Bridge deck photo-thermal super-hydrophobic solution, preparation method, dynamic spraying device and spraying control method

Abstract

The invention discloses a bridge floor photo-thermal super-hydrophobic solution, a preparation method, a dynamic spraying device and a spraying control method, and aims to solve the problem of icing of a bridge floor, improve the deicing efficiency and reduce damage to a bridge structure. The bridge deck photo-thermal super-hydrophobic solution is prepared from a traditional ice melting component, a corrosion inhibitor, a photo-thermal hydrophobic material, a phase solvent and a base material according to a proper proportion, has ice melting and super-hydrophobic performance, and can prevent ice and snow from being formed on a bridge deck. The dynamic spraying device comprises a bridge mounting bracket, a liquid storage tank, a connecting assembly capable of flexibly adapting to deformation, a polytetrafluoroethylene pipeline and an efficient spray head, and the uniformity and stability of a sprayed solution can be ensured. According to the spraying control method, environment data are monitored in real time through temperature, humidity, illumination and other sensors, the spraying amount and angle are adjusted through the intelligent control system, and efficient dynamic spraying is achieved. According to the invention, the cost and environmental pollution of the traditional deicing mode are reduced, the deicing strategy can be automatically adjusted according to climate change, and the application prospect is wide.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge ice suppression and de-icing, and specifically relates to a light-heat superhydrophobic aqueous solution for bridge decks, a preparation method, a dynamic spraying device, and a spraying control method. Background Technique

[0002] In winter, the environment where bridges are located is relatively special. The bridge deck structure causes the temperature of its underlying layer to be relatively low, and heat is dissipated rapidly. Compared with ordinary road surfaces, it is more likely to freeze. Taking the multiple rounds of heavy snow and freezing rain weather experienced in Hubei Province in 2024 as an example, during this period, the artificial working area on the bridge deck quickly froze within a very short time after the freezing rain ended, and even there was a difficult situation of "freezing within less than ten minutes after the freezing rain stopped, and the de-icing speed was far slower than the icing speed". Once the bridge deck freezes, traffic order will be severely disrupted, and traffic jams are extremely likely to occur. This not only affects everyone's daily travel but also hinders the passage of emergency rescue vehicles, posing a great threat to the safety and smoothness of transportation.

[0003] In traditional bridge deck de-icing methods, the application of snow melting salt materials is relatively widespread, but it has many drawbacks. The main components of snow melting salt (such as sodium chloride) are highly corrosive. During the process of melting ice and snow, it will cause serious erosion to bridge deck structural materials such as steel and concrete. This will not only reduce the durability of the reinforced concrete structure of the bridge but also increase the maintenance cost of the bridge, bringing potential safety hazards. Moreover, under low-temperature ice and snow weather conditions, snow removal machinery is restricted by the special environment of the bridge deck and often has difficulty entering the operation smoothly, further exacerbating the adverse effects caused by the icing of the bridge deck.

[0004] Although in the existing technical field, certain achievements have been made in the research on bridge deck anti-icing, there are still many deficiencies. Some research focuses on road surface anti-icing technology, and the special reasons for the bridge deck freezing first compared to the road surface are not analyzed thoroughly enough, lacking effective solutions specifically for the bridge deck situation. In the research on the temperature field of asphalt concrete bridge deck pavement structures, the research on the influence of paving materials, especially new materials, on the temperature field is relatively less, making it extremely difficult to fundamentally solve the problem of bridge deck icing. Additionally, in the research field of anti-icing asphalt mixtures, most still stay in traditional methods such as incorporating rubber particles and salt-storing materials, the research on the thermal conductivity of the mixtures is not deep enough, and rarely involves the construction of calculation models for the service life of materials and the effective de-icing service life, making it difficult to meet the long-term needs in practical applications.

[0005] In summary, the problem of bridge deck icing is currently severe, the drawbacks of traditional de-icing methods are obvious, and existing research cannot effectively solve this difficult problem. Based on such a background, the present invention is committed to developing a brand-new photothermal superhydrophobic aqueous solution, preparation method, dynamic spraying device, and spraying control method applicable to bridge deck ice inhibition and de-icing, with the expectation of providing a comprehensive bridge deck de-icing solution that is efficient, environmentally friendly, and can function stably in the long term. Summary of the Invention

[0006] The technical problem to be solved by the present invention is: in order to effectively solve the problem of bridge deck icing, improve the de-icing efficiency and reduce the damage to the bridge structure, the present invention discloses a photothermal superhydrophobic aqueous solution for bridge decks, a preparation method, a dynamic spraying device, and a spraying control method. The ice inhibition and de-icing principle of the photothermal superhydrophobic aqueous solution for bridge decks is based on the synergy of multiple components: sodium chloride and urea lower the freezing point and interfere with crystallization to accelerate ice melting; γ-aminopropyltriethoxysilane (KH-550), carbon black nanoparticles, expanded graphite, and methyltriethoxysilane (MTES) construct a superhydrophobic surface, reducing the residence and accumulation of water and reducing the possibility of icing; carbon black nanoparticles and expanded graphite perform photothermal conversion to increase the temperature and accelerate ice melting; sodium monofluorophosphate is used for corrosion inhibition to protect the bridge structure; ethanol is used as a phase solvent to promote the uniform dispersion and synergy of each component; the dedicated dynamic spraying device realizes ice inhibition and de-icing through customized bridge deck spraying devices, intelligent perception, precise regulation, and continuous maintenance, and can ensure the uniformity and stability of the sprayed solution; the spraying control method real-time monitors environmental data through sensors such as temperature, humidity, and light, and the intelligent control system adjusts the spraying amount and angle to achieve efficient dynamic spraying. The present invention reduces the cost and environmental pollution of traditional de-icing methods, can automatically adjust the de-icing strategy according to climate changes, and has a wide range of application prospects.

[0007] The technical solutions adopted by the present invention to solve the technical problems are as follows: A photothermal superhydrophobic aqueous solution for bridge decks is composed of traditional ice melting components, corrosion inhibitors, photothermal hydrophobic materials, phase solvents, and a matrix; the traditional ice melting components include sodium chloride and urea, the mass percentage of sodium chloride is 2% - 4%, and the mass percentage of urea is 1% - 2%; the corrosion inhibitor is sodium monofluorophosphate, with a mass percentage of 0.2% - 0.4%; the photothermal hydrophobic material is composed of a composite of γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite, and methyltriethoxysilane. Among them, the mass percentage of γ-aminopropyltriethoxysilane is 0.5% - 1.1%, the mass percentage of carbon black nanoparticles is 2% - 4%, the mass percentage of expanded graphite is 2% - 3%, and the mass percentage of methyltriethoxysilane is 2% - 3%; the phase solvent is ethanol, with a mass percentage of 3% - 5%; the matrix is water, and the mass percentage of water is 77.6% - 85.06%.

[0008] The method for preparing the bridge deck photothermal super-hydrophobic solution comprises the following specific steps: A. Raw material preparation: accurately weigh the following raw materials by mass percentage: 2% to 4% sodium chloride, 1% to 2% urea, 0.2% to 0.4% sodium monofluorophosphate corrosion inhibitor, 0.5% to 1.1% γ-aminopropyltriethoxysilane, 2% to 4% carbon black nanoparticles, 2% to 3% expanded graphite, 2% to 3% methyltriethoxysilane, 3% to 5% ethanol phase solvent, 77.6% to 85.06% matrix aqueous solution; B. Mixed dissolution: first add the weighed sodium chloride and urea into the ethanol phase solvent and stir to disperse, then add the sodium monofluorophosphate corrosion inhibitor and mix well, then add γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite and methyltriethoxysilane in sequence and stir well; C. Subsequent treatment: Let the solution stand and observe, if there are impurities, filter them out to finally obtain a photothermal superphobic aqueous solution.

[0009] The prepared dynamic spraying device for bridge deck photothermal super-phobic aqueous solution comprises a bridge mounting bracket, a nozzle assembly, a solution delivery branch pipeline, a solution delivery main pipeline, a liquid storage tank and a connecting assembly, wherein the curve shape of the bridge mounting bracket matches the curve shape of the bridge structure and is fixedly mounted on the bridge auxiliary structure by bolts; the liquid storage tank is fixedly arranged under the bridge hole by a hanger, and is provided with a liquid level sensor and an anti-sedimentation stirring device, the two ends of the hanger are fixed on the bridge structure, and the liquid level sensor and the anti-sedimentation stirring device are connected to the intelligent control system through a line; the connecting assembly adopts a metal bellows or a flexible rubber joint, one end of which is fixed on the bridge mounting bracket and the other end is firmly connected to the liquid storage tank, so as to ensure the normal operation of the spraying device when the bridge is deformed; the outlet of the liquid storage tank is sealedly connected to the solution delivery main pipeline through an elbow, the solution delivery main pipeline is sealedly connected to the solution delivery branch pipeline, the solution delivery branch pipeline is laid along the direction of the bridge and fixed to the bridge mounting bracket by a pipe clamp, and a plurality of nozzle assemblies are evenly arranged on the solution delivery branch pipeline; an intelligent flow regulating valve is arranged on the solution delivery main pipeline, and the intelligent flow regulating valve is electrically connected to the intelligent control system.

[0010] Preferably, the nozzle assembly includes a flow channel, a spiral guide blade, a dispersion plate, a reinforcing rib, a dispersion hole, a diffusion plate base, a diffusion plate, a radial guide groove, a tee, a nozzle solution delivery pipeline, an electric push rod, a ball joint, a nozzle mounting bracket and a mounting bolt hole. The nozzle solution delivery pipeline is sealed and connected to the solution delivery branch pipeline; the three ports of the tee are respectively connected to the inlet of the flow channel, the nozzle solution delivery pipeline and one end of the electric push rod; a spiral guide blade is welded on the inner side of the flow channel; a dispersion plate is fixedly provided at the end of the flow channel away from one end of the tee, The dispersion plate is evenly provided with dispersion holes; the diffuser is in the shape of a detachable bell mouth, connected to the front end of the nozzle by a thread, with a diffusion angle of 60°, and 6 radial guide grooves are evenly provided on the inner wall; one end of the electric push rod is connected to the tee, and the other end is fixedly connected to the nozzle mounting bracket by a ball joint, and the entire nozzle assembly is fixed to the bridge mounting bracket by bolts and mounting bolt holes; the reinforcing ribs are radial ribs with a thickness of 3 mm, 6 of which are evenly distributed along the outer wall of the nozzle and extend to the diffuser base, so as to enhance the structural strength of the nozzle and prevent deformation caused by high-pressure spraying.

[0011] Preferably, a stepper motor is provided in the electric push rod, and the stepper motor is connected to the intelligent control system through a waterproof cable, receives a PWM signal to adjust the extension amount and thus adjust the angle of the nozzle, thereby achieving precise control of the spraying angle. The ball joint adopts a stainless steel ball head and a polytetrafluoroethylene bearing seat, allowing the nozzle to rotate horizontally by ±45° and vertically by ±30°, playing a role of connection and flexible rotation during the nozzle angle adjustment process.

[0012] The spraying control method of the dynamic spraying device includes sensor data acquisition, data processing and analysis, feature construction and decision generation, remote monitoring and adaptive adjustment; The sensor data collection includes: measuring the bridge deck temperature value and calculating the temperature gradient through multi-point layout temperature sensors, and recording the temperature history data within 1 hour; using humidity sensors to distribute the bridge deck to monitor humidity and assist in analyzing the risk of icing; using light intensity sensors to feedback light intensity and evaluate the degree of utilization of photothermal effect; using ice thickness sensors to measure the thickness of ice on the bridge deck, and characterizing the development of ice by the thickness change rate; The data processing and analysis: firstly, the raw data of various sensors are collected and normalized to the interval of [0-1] by linear method to facilitate comprehensive calculation and analysis; then, the sliding average filtering algorithm is used to perform denoising on the raw data through a sliding window of length 5 to ensure the accuracy of the data; The feature construction and decision generation include: constructing icing risk features, estimating light and heat effect features, characterizing ice layer state features, and generating decisions. Based on a machine learning algorithm, the optimal spraying control strategy is generated by constructing icing risk factors, light and heat effect features, and ice layer state features. The remote monitoring and adaptive adjustment: It includes a remote monitoring function and an adaptive adjustment function; the remote monitoring function is connected to a remote monitoring platform through a 4G / 5G network connection device to view information such as the liquid level of the liquid storage tank, pipeline pressure, and sprinkler angle, and remotely modify the spraying parameters and control the start and stop of the device; the adaptive adjustment function dynamically optimizes the spraying control strategy according to the weather and the icing condition of the bridge, and adjusts parameters such as the spraying area and flow rate.

[0013] Preferably, in the process of data processing and analysis, the original data of various sensors are collected and normalized to the [0-1] interval by the linear method. For temperature, the formula: Tnorm=(T-Tmin) / (Tmax-Tmin ) (Tmin=-10 °C, Tmax=5 °C) is used for linear mapping to [0-1]; for humidity, percentage values are normalized (0-100% corresponds to [0-1]); for light intensity, it is normalized according to the maximum sunshine intensity in the region; the moving average filtering algorithm is fixed at 5 data points with a time interval of 1 minute. The noise is smoothed by historical data, and the head and tail data are filled by the mirror filling method to avoid edge data distortion, and the noise is reduced by 70%.

[0014] Preferably, in the process of feature construction and decision generation, the icing risk feature is constructed through a specific calculation formula, that is, the icing risk area is determined by the icing risk factor Frisk = normalized humidity value × (1 -| normalized temperature value - 0.5|), where 0 °C corresponds to the normalized value of 0.5; the estimation of the photo-thermal effect feature estimates the expected photo-thermal temperature rise value Fphoto according to the light intensity and the photo-thermal efficiency curve to assist in the spraying decision; the characterization of the ice layer state feature calculates the ice layer thickness change rate Fice to judge the development of the ice layer; the decision generation includes threshold setting, spraying order decision, sprinkler angle decision, flow rate decision, and spraying duration decision; among them, the threshold setting refers to setting the icing risk threshold Frisk, the photo-thermal effect threshold Fphoto, and the ice layer thickening related thresholds Tice1 and Tice2 (Tice1 < Tice2); the spraying order decision refers to determining the order according to the comparison of the feature indicators and the thresholds. Spraying the well-lit area with high icing risk first if the light is good, otherwise in the normal order; the sprinkler angle decision refers to adjusting the angle towards the light direction if the light is good and aiming at the easily iced parts if the icing risk is high; the flow rate decision refers to adjusting the flow rate according to the ice layer thickness change rate, large for large, medium for medium, and small for small; the spraying duration decision refers to determining the duration according to the icing risk and the ice layer thickening situation, long for high risk and fast thickening, and short otherwise.

[0015] Preferably, during the feature construction and decision-making generation process, the spraying control strategy includes preventive basic spraying, targeted enhanced spraying, and regular maintenance spraying; preventive basic spraying is initiated when winter is approaching or the temperature drops but does not freeze, spraying from the high to the low and from the center to both sides of the bridge, with a moderate flow rate to form a uniform coating, using the superhydrophobic and photothermal effects to prevent ice formation, increase the bridge deck temperature, and prevent icing; targeted enhanced spraying is triggered when the risk of ice layer or icing-prone area increases, adjusting the nozzle angle to align with the target, increasing the flow rate to accelerate melting, and increasing the spraying frequency according to the icing situation; based on the bridge usage, environmental data, and previous de-icing effects, regular maintenance spraying is carried out once a week, with full or partial spraying, and the flow rate and duration are adjusted according to the situation.

[0016] Preferably, the ice formation risk threshold Frisk is initially set to 0.6. If the ice formation frequency > 20%, the threshold is lowered to 0.55; the photothermal effect threshold Fphoto is set to 0.7 according to the light intensity and solution photothermal conversion efficiency curve; the ice layer thickening threshold: Tice1 = 0.05 mm / min for mild icing, triggering basic spraying; Tice2 = 0.1 mm / min for severe icing, triggering enhanced spraying; the spraying order decision: if Frisk ≥ 0.6 and Fphoto ≥ 0.7, give priority to spraying the area with sufficient light, using the photothermal effect to accelerate ice melting; if Frisk ≥ 0.6 but the light is insufficient, spray according to the ice layer thickness change rate; the nozzle angle decision: ±45° in the horizontal direction and ±30° in the vertical direction, adjusted in real time through the PID algorithm to ensure coverage of the target area; the spraying flow rate decision: the basic flow rate is 5 L / min, and for every 0.01 mm / min increase in the ice layer thickening rate, the flow rate is increased by 10%; the spraying duration decision: spraying duration = ice layer thickness / (flow rate × solution ice melting efficiency), where the ice melting efficiency is calibrated to 0.8 mm / L.

[0017] Preferably, the bridge deck photothermal superhydrophobic aqueous solution is composed of traditional ice melting components, corrosion inhibitors, photothermal hydrophobic materials, phase solvents, and water. The proportions of each component can be adjusted within a certain range, and the specific proportions are determined according to experimental data and actual application requirements to ensure the stability and effectiveness of the solution in different environments.

[0018] Preferably, the traditional ice melting components are selected as a combination of sodium chloride and urea. The mass percentage of sodium chloride is 2% - 4%, and the mass percentage of urea is 1% - 2%. After sodium chloride dissolves, it can change the properties of the aqueous solution to lower the freezing point and melt ice. Urea melts ice by forming hydrogen bonds with water molecules to interfere with the crystallization process. The two work together to enhance the ice melting effect, while controlling costs, reducing corrosion of the road surface, and environmental pollution.

[0019] Preferably, the corrosion inhibitor is selected as sodium monofluorophosphate (MFP) with a mass percentage of 0.2% - 0.4%. Sodium monofluorophosphate has good chemical stability and exhibits excellent corrosion inhibition performance in neutral and weakly acidic environments. It can form a protective film on the metal surface, effectively slowing down the metal corrosion in the environment containing chloride ions.

[0020] Preferably, the photothermal superhydrophobic material is composed of γ-aminopropyltriethoxysilane (KH-550), carbon black nanoparticles, expanded graphite, and methyltriethoxysilane (MTES). Among them, γ-aminopropyltriethoxysilane (KH - 550) has a mass percentage of 0.5% - 1.1%. As a silane coupling agent, it can enhance the binding force between components. By reacting or adsorbing with the surface functional groups of other hydrophobic materials, it constructs a microscopically rough structure, which can not only improve the superhydrophobic performance but also enhance the adhesion between the coating and the substrate. Carbon black nanoparticles have a mass percentage of 2% - 4%. As a photothermal conversion material, the surface functional groups on it can react or adsorb with the silane coupling agent and participate in the construction of the hydrophobic film. Due to its large specific surface area, it can construct a microscopically rough structure and also has photothermal conversion performance. Moreover, carbon black nanoparticles have a wide source and low cost, which is conducive to large-scale application. Expanded graphite has a mass percentage of 2% - 3%. As a material for constructing a microscopically rough structure and a heat-conducting material, it retains the flaky structure of graphite, which helps to construct a microscopically rough structure, thus achieving superhydrophobicity. Its functional groups can react with the silane coupling agent to enhance stability. In terms of heat conductivity, it can cooperate with carbon black to improve the photothermal performance and at the same time provide an attachment site for methyltriethoxysilane (MTES) to form a hydrophobic film. Methyltriethoxysilane (MTES) has a mass percentage of 2% - 3%. As a low surface energy material, it forms a hydrophobic organosilicon film through hydrolysis and condensation, reducing the surface energy to achieve superhydrophobicity. The photothermal superhydrophobic material is environmentally friendly, has a reasonable cost, and has good long-term use stability.

[0021] Preferably, the phase solvent is selected as ethanol with a mass percentage of 3% - 5%. As a material phase solvent, it has good solubility and dispersibility for the system components, can prevent agglomeration and precipitation, and promote the functions of each component.

[0022] Preferably, the mass percentage of water is 77.6% - 85.06%. As the matrix of the photothermal superhydrophobic aqueous solution, it is prepared into a solution for easy spraying.

[0023] The principle of ice inhibition and de-icing of the photothermal superhydrophobic aqueous solution on the bridge deck in the present invention is as follows: 1. The interaction between traditional ice-melting materials and hydrophobic materials: On the one hand, the superhydrophobic surface formed by the hydrophobic material can reduce the residence and accumulation of water on the coating, reducing the possibility of icing. On the other hand, in case ice forms, the ice-melting material can accelerate the melting of ice, jointly ensuring the hydrophobic and ice-inhibiting effect of the coating.

[0024] 2. Interaction between traditional ice-melting materials and co-solvent (ethanol): As a co-solvent, ethanol helps traditional ice-melting materials dissolve and disperse better in the whole system, avoiding affecting the overall ice inhibition effect due to uneven local concentration.

[0025] 3. Interaction between hydrophobic materials and co-solvent (ethanol): For the photothermal hydrophobic material composed of γ-aminopropyltriethoxysilane (KH-550), carbon black nanoparticles, expanded graphite (EG), and methyltriethoxysilane (MTES), ethanol can improve their solubility and dispersibility.

[0026] 4. Interaction between components of hydrophobic materials: (1) γ-aminopropyltriethoxysilane (KH-550): As a silane coupling agent, KH-550 can combine with functional groups (such as hydroxyl groups, carboxyl groups, etc.) on the surfaces of carbon black nanoparticles and expanded graphite through chemical actions (such as hydrogen bonding, amidation reaction, condensation reaction, etc.) and physical adsorption, providing a good adhesion basis for them in the coating system, making them disperse evenly, and jointly constructing a microscopic rough structure, which is crucial for achieving superhydrophobic performance and helps enhance the adhesion between the coating and the substrate, improving the overall coating performance.

[0027] (2) Carbon black nanoparticles: The functional groups on its surface can undergo chemical reactions or physical adsorption with silane coupling agents (such as KH-550, methyltriethoxysilane (MTES)), participating in the construction process of the hydrophobic film, enhancing the uniformity and stability of the hydrophobic film, and thus improving the superhydrophobic effect. At the same time, the large specific surface area of carbon black nanoparticles can construct a microscopic rough structure, and they have photothermal properties, which can cooperate with expanded graphite to improve the photothermal performance of the coating, ensuring the stability of the superhydrophobic surface at different environmental temperatures.

[0028] (3) Expanded graphite (EG): On the one hand, expanded graphite can construct a microscopic rough structure conducive to the realization of superhydrophobic performance by virtue of the graphite characteristics retained in its flaky structure, and the functional groups on its surface can undergo condensation reactions with silanols generated by the hydrolysis of silane coupling agents (such as KH-550, MTES), achieving chemical bonding with the coating system and enhancing its stability in the coating; on the other hand, during the formation of the hydrophobic film by methyltriethoxysilane (MTES), the flaky structure of expanded graphite can provide more attachment sites for it, making the hydrophobic film form more evenly and densely, improving the hydrophobic effect, and cooperating with other hydrophobic materials such as carbon black nanoparticles to ensure the overall performance of the superhydrophobic composite material.

[0029] (4)Methyltriethoxysilane (MTES): It forms a hydrophobic silicone film on the coating surface through hydrolysis and condensation reactions, reduces the surface energy of the coating to achieve superhydrophobic effect, cooperates with other hydrophobic materials to improve the construction of the hydrophobic structure, jointly enhances the superhydrophobic performance, and has good environmental performance and reasonable cost, meeting the requirements of the entire composite system.

[0030] The chemical reaction equations involved in the ice inhibition and de-icing process of the photothermal superhydrophobic aqueous solution in the present invention are as follows: 1. Dissolution and ionization of sodium chloride: NaCl - Na + + Cl - 2. Hydrogen bond interaction between urea and water molecules (schematic): H2N - CO - NH2…H - O - H 3. Reaction between sodium monofluorophosphate and iron ions (example): 2Na2PO3F + 3Fe 2+ →Fe(PO3F)2↓ + 4Na + 4. Amidation reaction between KH - 550 and carboxyl - containing substances (example): R - COOH + H2N-(CH2)3 - Si(OH)3 → R - CONH -(CH2)3 - Si(OC2H5)3 + H2O 5. Ethoxy hydrolysis reaction of KH - 550: Si(OC2H5)3-(CH2)3 - NH2 + H2O → Si(OH)3-(CH2)3 - NH2 + C2H5OH 6. Condensation reaction of KH - 550 (schematic of polymerization): Si(OH)3-(CH2)3 - NH2 + Si(OH)3-(CH2)3 - NH2 → (Si - O - Si) n + H2O 7. Condensation reaction between expanded graphite and hydrolyzed silicon hydroxyl groups of KH - 550 (example): R - COOH + Si(OH)3-(CH2)3 - NH2 → R - COO - Si(OH)2 - (CH2)3 - NH2 + H2O 8. Hydrolysis reaction of MTES: Si(OC2H5)3 - R + 3H2O → Si(OH)3 - R + 3C2H5OH 9. Condensation reaction of MTES (schematic of film formation): Si(OH)3 - R + Si(OH)3 - R → (Si - O - Si) n - R + H2O The innovative design of the dynamic spraying device and spraying control method in the present invention: 1. The overall structure of the dynamic spraying device includes: a customized bridge mounting bracket, a connection component that can flexibly adapt to deformation, a special liquid storage tank, a solution delivery pipeline, and a special nozzle assembly.

[0031] The customized bridge mounting bracket is made of high-strength aluminum alloy, which can bear the load and withstand environmental changes; the bridge mounting bracket is customized according to the bridge structure, such as the box girder bridge bracket fits the bottom and side curves, and the arch bridge bracket is designed according to the arch. The installation design uses the reserved position or auxiliary structure of the bridge, and is firmly installed with fastening clamps and bolts to ensure horizontality and verticality.

[0032] The connection component that can flexibly adapt to deformation adopts metal bellows or flexible rubber joints, which are located between the bracket and the device body, and adjust with the expansion and contraction and vibration of the bridge to ensure the stability of the device and buffer vibration. The installation design has one end reliably connected to the bracket and the other end firmly sealed with the liquid storage tank or the starting end of the delivery pipeline to ensure the normal operation of the device when the bridge deforms.

[0033] The special liquid storage tank is made of polycarbonate (PC) and its shape fits the space under the bridge. It has a liquid level sensor and an anti-sedimentation stirring device to monitor the liquid level and prevent sedimentation to ensure that the solution is uniform and stable. The installation design uses hangers and brackets to fix it at a suitable position, and connects the liquid level sensor and the anti-sedimentation stirring device to the intelligent control system through lines.

[0034] The solution delivery pipeline is made of polytetrafluoroethylene, which has good compatibility with the solution, smooth inner wall, light and heat resistance, reduces delivery resistance, prevents impurities from adhering, and is equipped with an intelligent flow regulating valve to control the flow. The installation design is laid from the outlet of the liquid storage tank along the direction of the bridge, fixes and connects the pipes to ensure sealing, installs the intelligent flow regulating valve and makes electrical connections.

[0035] The special nozzle assembly is made of copper alloy or stainless steel, and is composed of flow channels, spiral guide blades, dispersion holes, diffusers, electric push rods, ball joints, reinforcing ribs and other parts. The installation design uses a specially designed stainless steel nozzle mounting bracket to fix the nozzle on the bridge structure. The bracket is connected by welding or bolts to ensure a firm installation; the nozzle delivery pipe and the solution delivery pipeline are connected by a three-way connection with good sealing performance to ensure that the solution is delivered to the nozzle without leakage; one end of the electric push rod is connected to the nozzle, and the other end is fixed to the mounting bracket by a ball joint to adjust the angle of the nozzle. The push rod has a built-in stepper motor and is connected to the intelligent control system through a waterproof cable. It receives PWM signals to adjust the extension and contraction amount to adjust the angle of the nozzle, thereby achieving precise control of the spraying angle. The ball joint plays a role in connection and flexible rotation during the nozzle angle adjustment process.

[0036] The flow channel can effectively prevent blockage. The inner wall of the flow channel is coated with a polytetrafluoroethylene coating to reduce solution adhesion and ensure smooth passage of the solution. The flow channel inlet is sealed and connected to the polytetrafluoroethylene delivery pipe through a three-way joint, and an O-type rubber ring (corrosion-resistant material) is used at the interface to prevent leakage.

[0037] The guide vane is a spiral stainless steel sheet welded to the inner side of the flow channel, which can guide the flow direction of the solution so that it is evenly distributed inside the nozzle.

[0038] The dispersion holes are located behind the guide vanes and are embedded in the middle of the nozzle by snapping. They can be removed and replaced individually. The aperture gradually decreases from the center to the outer edge (1.5mm→0.5mm) and are distributed in a circular array with 3 layers and 12 holes in each layer, ensuring uniform refinement of the droplets and improving the uniformity of spraying.

[0039] The diffuser is in the shape of a detachable bell mouth (stainless steel stamping), connected to the front end of the nozzle by a thread, with a diffusion angle of 60° and 6 radial guide grooves (depth 2mm) on the inner wall to expand the spraying range so that the solution can cover a larger bridge surface area.

[0040] The electric push rod is hinged to the rear of the nozzle through an L-shaped connecting rod, and the other end is fixed to the mounting bracket through a ball joint to adjust the angle of the nozzle. The push rod has a built-in stepper motor, which is connected to the intelligent control system through a waterproof cable and receives a PWM signal to adjust the extension and retraction amount.

[0041] The ball joint adopts a stainless steel ball head matched with a polytetrafluoroethylene bearing seat, allowing the nozzle to rotate horizontally ±45° and vertically ±30°, ensuring that the nozzle can rotate flexibly when adjusting the angle.

[0042] The reinforcing ribs are radial ribs (3 mm thick), 6 of which are evenly distributed along the outer wall of the nozzle and extend to the base of the diffuser to enhance the structural strength of the nozzle and prevent deformation caused by high-pressure spraying.

[0043] 2. Spraying control methods include sensor data acquisition, data processing and analysis, feature construction and decision generation, remote monitoring and adaptive adjustment.

[0044] ① The sensor data collection uses temperature sensors to be distributed on the bridge deck at multiple points to measure temperature values ​​and calculate temperature gradients, and record temperature history data within 1 hour; humidity sensors are distributed on the bridge deck to monitor humidity and assist in analyzing icing risks; light intensity sensors are installed in appropriate locations to feedback light intensity and evaluate the degree of utilization of photothermal effects; ice thickness sensors: measure the thickness of ice on the bridge deck, calculate the thickness change rate to characterize the development of the ice layer, The temperature sensor has an accuracy of up to ±0.5°C to ensure the accuracy of the collected data. The preferred installation locations are the shady side of the bridge deck, the windward side of the bridge deck, the center area of ​​the bridge deck, etc. For example, it is installed near the bridge piers and the bottom of the bridge, with one sensor arranged every 5 meters to monitor low-temperature and icing-prone areas; one sensor is arranged every 10 meters on both sides of the bridge to monitor temperature changes caused by wind cooling effects; one sensor is arranged every 15 meters in the center area of ​​the bridge deck to cover the overall temperature distribution of the bridge deck. The installation method can be embedded 1 to 2 cm below the surface of the bridge deck to avoid damage caused by vehicle crushing, while ensuring direct contact with the bridge deck for accurate temperature measurement; The humidity sensor has an accuracy of ±3% RH to ensure the accuracy of the collected data. The preferred installation location is the low-lying area of ​​the bridge deck or the bottom of the bridge. For example, it can be installed near the drain outlet or the edge of the expansion joint, with one sensor arranged every 5 meters to monitor the humidity changes caused by water accumulation; where condensation water is prone to accumulate, one sensor can be arranged every 10 meters. The installation method can be selected to be mounted on the surface of the bridge deck, with the sensor probe exposed to the air and in direct contact with the ambient moisture; The light intensity sensor has an accuracy of ±10W / m² to ensure the accuracy of the collected data. The preferred installation location is the top of the guardrails on both sides of the bridge deck, with one sensor arranged every 20 meters to ensure unobstructed sunlight reception; or the top of the bridge (such as the top of the arch bridge), with 1 to 2 sensors installed to monitor the overall light intensity. The installation method can be fixed to the guardrail or the top of the bridge through a bracket, with the sensor tilted upward by 30° to avoid shadows; The ice thickness sensor has an accuracy of ±0.5mm to ensure the accuracy of the collected data. The installation location is preferably the key position that is easy to freeze and the ice thickness changes significantly, such as the expansion joint of the bridge, the low-lying water accumulation area, the connection between the ramp and the main bridge, and the area where the bridge deck is not drained. For example, at the expansion joint of the bridge, one is arranged every 2 meters to accurately monitor the changes in the ice layer caused by the expansion and contraction of the bridge structure; in the low-lying water accumulation area, one is arranged every 3 to 5 meters at the center and the edge according to the size of the water accumulation area, and the change in ice thickness caused by the rapid freezing of the water is closely monitored; on both sides and in the middle of the connection between the ramp and the main bridge, one is arranged every 5 meters to timely grasp the dynamics of ice thickness in the iced area caused by changes in vehicle driving status and slope differences; near the drainage holes in the area where the bridge deck is not drained well and the low-lying points where the water flow converges, one is arranged every 4 meters to focus on monitoring the changes in ice after the water accumulates and freezes due to drainage problems. The installation method is to pre-open a 3-5cm deep installation hole at a specific location on the bridge deck, install the sensor probe vertically in the hole, make its bottom in close contact with the bridge deck, and seal it with sealant to prevent moisture and debris from affecting the measurement accuracy. The sensor body is fixed on the structure under the bridge deck and connected to the intelligent control system through a cable to ensure stable signal transmission and achieve accurate monitoring of ice thickness.

[0045] ② For the data processing and analysis, first, the original data of various sensors are collected and normalized to the range of [0 - 1] using the linear method for convenient comprehensive operation and analysis. Then, the sliding average filtering algorithm is adopted in the data processing and analysis part. The original data are denoised through a sliding window with a length of 5 to ensure the accuracy of the data. Furthermore, for collecting the original data of various sensors and normalizing them to the range of [0 - 1] using the linear method, the temperature is linearly mapped to [0 - 1] using the formula: Tnorm=(T - Tmin) / (Tmax - Tmin) (where Tmin = -10 °C and Tmax = 5 °C); the humidity is directly normalized using the percentage value (0 - 100% corresponds to [0 - 1]); the light intensity is normalized according to the maximum sunshine intensity in the region (such as 1000 W / m²). The sliding average filtering algorithm is fixed at 5 data points (with a time interval of 1 minute). The noise is smoothed through historical data. The head and tail data are filled using the mirror filling method to avoid distortion of the edge data, and the noise is reduced by 70%.

[0046] ③ The feature construction and decision generation include the construction of ice formation risk features, the estimation of photothermal effect features, the characterization of ice layer state features, and decision generation. The feature construction and decision generation part is based on machine learning algorithms. Through the construction of ice formation risk factors, photothermal effect features, and ice layer state features, the optimal spraying decision is generated. Among them, the construction of ice formation risk features is to determine the ice formation risk area through a specific calculation formula, that is, the ice formation risk factor Frisk = normalized humidity value × (1 - |normalized temperature value - 0.5|) (assuming that 0 °C corresponds to the normalized value of 0.5); the estimation of photothermal effect features is to estimate the expected photothermal temperature rise value Fphoto according to the light intensity and the photothermal efficiency curve to assist in the spraying decision; the characterization of ice layer state features is to calculate the ice layer thickness change rate Fice to judge the development of the ice layer; the decision generation includes threshold setting, spraying order decision, nozzle angle decision, flow rate decision, and spraying duration decision. Among them, the threshold setting specifically refers to setting the ice formation risk threshold Frisk, the photothermal effect threshold Fphoto, the ice layer thickening related thresholds Tice1 and Tice2 (Tice1 < Tice2); the spraying order decision specifically refers to determining the order by comparing the characteristic indicators with the thresholds. Spraying the well-lit area with high ice formation risk first if the light is good, otherwise in the normal order; the nozzle angle decision specifically refers to adjusting the nozzle towards the light direction if the light is good and aiming at the easily frozen parts if the ice formation risk is high; the flow rate decision specifically refers to adjusting the flow rate according to the ice layer thickness change rate, with a large rate for a large change, a medium rate for a medium change, and a small rate for a small change; the spraying duration decision specifically refers to determining the duration according to the ice formation risk and the ice layer thickening situation, with a long duration for high risk and fast thickening, and a short duration otherwise.

[0047] Furthermore, for the specific calculation formula for constructing the icing risk characteristics, the icing risk factor calculation formula proposed in the present invention is F risk = humidity normalization value × (1 - |temperature normalization value - 0.5|), which is an original design. The temperature normalization value corresponds to 0.5 at 0 °C (assuming the temperature range is -10 °C to 5 °C, and the normalization formula is: (T + 10) / 15). The higher the humidity, the greater the icing risk; when the temperature is close to the freezing point (the normalization value is close to 0.5), the icing risk is the highest. This is significantly different from the prior art's judgment method based on a single temperature and humidity threshold. By quantifying the degree of the temperature approaching the freezing point through the normalized offset of the temperature from the freezing point (0 °C) (|temperature normalization value - 0.5|) and combining with the humidity weight to construct a non-linear correlation model, it can more accurately reflect the dynamic risk of bridge deck icing.

[0048] Furthermore, for the icing risk factor calculation formula, based on the actual bridge deck data during the heavy snow and freezing rain in Hubei Province in 2024, the formula can be verified: when F risk ≥ 0.6, the icing probability reaches 92.3% (the control group is 84.1% of the traditional linear model), and the error is reduced by 8.2%. The specific experimental data is as follows: Temperature (°C) Humidity (%) <![CDATA[F risk > Actual icing (Yes / No) -5 80 0.73 Yes 0 65 0.60 Yes 2 85 0.42 No Regarding the threshold setting, the icing risk threshold F risk : Initially set to 0.6, and dynamically adjusted according to historical data (such as the frequency of icing events in the past 24 hours). If the icing frequency > 20%, the threshold is lowered to 0.55; the photothermal effect threshold F photo : Set to 0.7 according to the curve of light intensity and the photothermal conversion efficiency of the solution; the ice layer thickening threshold: T ice1 = 0.05 mm / min (light icing, triggering basic spraying); T ice2 = 0.1 mm / min (severe icing, triggering enhanced spraying); Regarding the spraying sequence decision, if F risk ≥ 0.6 and F photo ≥ 0.7, give priority to spraying the areas with sufficient light, and utilize the photothermal effect to accelerate ice melting; if F risk ≥ 0.6 but there is insufficient light, spray in the order of the ice layer thickness change rate; Regarding the nozzle angle decision, it is ±45° in the horizontal direction and ±30° in the vertical direction, and is adjusted in real time through the PID algorithm to ensure coverage of the target area; Regarding the spraying flow rate decision, the basic flow rate is 5 L / min, and for every increase of 0.01 mm / min in the ice layer thickening rate, the flow rate is increased by 10%; Regarding the spraying duration decision, the spraying duration = ice layer thickness / (flow rate × solution ice melting efficiency) (the ice melting efficiency is calibrated in the laboratory to be 0.8 mm / L).

[0049] ④ Remote monitoring and adaptive adjustment module control method, including remote monitoring function and adaptive adjustment function. The remote monitoring function uses 4G / 5G network to connect the device to the remote monitoring platform to view information such as the liquid level of the storage tank, pipeline pressure, nozzle angle, etc., remotely modify the spraying parameters and control the start and stop of the device. The adaptive adjustment function dynamically optimizes the spraying strategy according to the weather and bridge icing conditions, and adjusts the spraying area, flow rate and other parameters.

[0050] ⑤Spraying control strategies in different scenarios include: preventive basic spraying, targeted enhanced spraying, and regular maintenance spraying.

[0051] The preventive basic spraying is timed to start when winter comes or the temperature drops but no ice forms; the spraying sequence and flow rate are controlled from high to low points of the bridge and from the center to both sides, with a moderate flow rate to form a uniform coating; the expected effect is to use super-hydrophobic and photothermal effects to prevent water icing, increase the bridge deck temperature, and prevent icing.

[0052] The targeted enhanced spraying monitors trigger conditions and is triggered when the risk of ice or icing-prone areas increases; spraying parameters are adjusted, the angle of the nozzle is adjusted to align with the target, the flow rate is increased to accelerate melting, and the spraying frequency is increased depending on the situation.

[0053] The regular maintenance spraying has a spraying cycle determined by comprehensive bridge usage, environmental data and previous results, generally once a week, which can be adjusted; the spraying range and parameters can be adjusted, and it can be comprehensive or partial spraying, and the flow and duration can be adjusted according to the situation.

[0054] The present invention has many positive and beneficial effects: First, efficient ice suppression and de-icing: through a unique material formula design, the synergistic effect of ice-melting ingredients (sodium chloride and urea) effectively lowers the freezing point of water and accelerates the melting of ice in a low-temperature environment. It is low-cost, economical and environmentally friendly. The super-hydrophobic surface formed by hydrophobic materials (carbon black nanoparticles, expanded graphite, γ-aminopropyltriethoxysilane (KH-550), methyltriethoxysilane (MTES)) reduces the retention and accumulation of water and reduces the possibility of icing. The addition of photothermal conversion nanomaterials and high thermal conductivity expanded graphite, the combination of the two significantly improves the efficiency of ice suppression and de-icing on the bridge deck, ensuring the safe passage of the bridge in low temperature weather.

[0055] Secondly, corrosion inhibitors are added to protect bridge structures: the application of corrosion inhibitor sodium monofluorophosphate in the material system can form a protective film on the metal surface, effectively slowing down the corrosion of metals in chloride ion environments (from sodium chloride), reducing the risk of erosion of traditional snow-melting salt on steel, concrete and other bridge structure materials, extending the service life of bridges and reducing maintenance costs.

[0056] In the third aspect, precise intelligent control is achieved. Based on the data collected by various sensors such as temperature, humidity, light intensity, and ice layer thickness arranged on the bridge deck, after normalization processing and filtering to remove noise, features such as icing risk, photothermal effect, and ice layer state are constructed, and thresholds are set accordingly for decision-making generation. The spraying sequence, nozzle angle, flow rate, and spraying duration can be accurately determined according to the actual conditions of different regions, realizing intelligent and targeted spraying operations, improving resource utilization efficiency, and optimizing the deicing effect.

[0057] In the fourth aspect, the calculation formula for the icing risk factor proposed in the present invention (F risk = normalized humidity value × (1 - |normalized temperature value - 0.5|)) is an original design, which is significantly different from the existing judgment methods based on single temperature and humidity thresholds. The degree of temperature approaching the freezing point is quantified by the normalized offset of temperature from the freezing point (0°C) (|normalized temperature value - 0.5|), and a non-linear correlation model is constructed by combining the humidity weight, which can more accurately reflect the dynamic risk of bridge deck icing.

[0058] In the fifth aspect, there is a design for a spraying device with a dedicated bridge environment. The customized bridge installation bracket is customized according to the bridge structure form and is made of high-strength aluminum alloy material to ensure the stable installation of the device and its resistance to environmental changes. The flexible connection components (metal bellows or flexible rubber joints) that can adapt to deformation can effectively cope with bridge expansion and vibration, ensuring the overall stability of the device. Components such as the special liquid storage tank, polytetrafluoroethylene delivery pipeline, and special nozzles fully consider the characteristics of photothermal superhydrophobic materials and the installation and use requirements of the bridge in terms of material selection and structural design, ensuring the long-term stable operation of the device and the effective spraying of the solution.

[0059] In the sixth aspect, remote monitoring and adaptive adjustment are achieved. With the help of wireless communication technology, remote monitoring is realized. Managers can always master the operation status of the device and remotely modify the spraying parameters and control the start and stop of the device, improving the flexibility to respond to emergencies. At the same time, the system can automatically optimize the spraying strategy according to the weather conditions and the actual icing situation of the bridge, dynamically adjust parameters such as the spraying area and flow rate, and always maintain a good ice suppression and deicing effect to adapt to the complex and changeable actual environment.

[0060] In the seventh aspect, it has environmental protection and cost-effectiveness. The material selection pays attention to the balance between environmental protection and cost, such as the biodegradability of urea, the environmental protection performance of methyltriethoxysilane (MTES), and the reasonable cost control of each component. While achieving effective ice suppression and deicing, it reduces the negative impact on the environment and resource waste, and has good economic and environmental benefits. Description of the Drawings

[0061] Figure 1 It is a schematic structural diagram of the dynamic spraying device in the present invention; Figure 2It is a schematic structural diagram of the nozzle assembly in the present invention; In Figure 1 and Figure 2 1 - Bridge installation bracket, 2 - Nozzle assembly, 3 - Bolt, 4 - Bridge accessory structure, 5 - Solution delivery branch pipe, 6 - Pipe clamp, 7 - Solution delivery main pipe, 8 - Intelligent flow regulating valve, 9 - Elbow, 10 - Hanger, 11 - Liquid level sensor, 12 - Liquid storage tank, 13 - Anti-precipitation stirring device, 14 - Connection assembly; 201 - Flow channel, 202 - Spiral guide vane, 203 - Dispersion plate, 204 - Reinforcing rib, 205 - Dispersion hole, 206 - Diffusion plate base, 207 - Diffusion plate, 208 - Radial guide groove, 209 - Tee, 210 - Nozzle solution delivery pipe, 211 - Electric push rod, 212 - Ball hinge, 213 - Nozzle installation bracket, 214 - Installation bolt hole.

[0062] Figure 3 It is a principle block diagram of the connection between each sensor in the present invention and the intelligent control system and the remote monitoring platform; Figure 4 It is a schematic diagram of the amidation reaction mechanism of KH-550 and carboxyl-containing substances and the hydrolysis reaction mechanism of KH-550 ethoxy group in the present invention; Figure 5 It is a schematic diagram of the condensation reaction mechanism of KH-550 in the present invention; Figure 6 It is a schematic diagram of the condensation reaction mechanism of expanded graphite and KH-550 hydrolyzed silicon carboxyl group and the reaction mechanism of sodium monofluorophosphate and iron ions in the present invention; Figure 7 It is a schematic diagram of the condensation reaction mechanism of MTES and the hydrolysis reaction mechanism of MTES in the present invention. Specific embodiments

[0063] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the technical solutions of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0064] A bridge deck photothermal super-phobic solution is composed of a traditional ice-melting component, a corrosion inhibitor, a photothermal hydrophobic material, a phase solvent and a matrix; the traditional ice-melting component includes sodium chloride and urea, the mass percentage of the sodium chloride is 2% to 4%, and the mass percentage of the urea is 1% to 2%; the corrosion inhibitor is sodium monofluorophosphate, and the mass percentage is 0.2% to 0.4%; the photothermal hydrophobic material is composited by γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite, and methyltriethoxysilane, wherein the mass percentage of γ-aminopropyltriethoxysilane is 0.5% to 1.1%, the mass percentage of carbon black nanoparticles is 2% to 4%, the mass percentage of expanded graphite is 2% to 3%, and the mass percentage of methyltriethoxysilane is 2% to 3%; the phase solvent is ethanol, and the mass percentage is 3% to 5%; the matrix is ​​water, and the mass percentage of the water is 77.6% to 85.06%.

[0065] The method for preparing the bridge deck photothermal super-hydrophobic solution comprises the following specific steps: A. Raw material preparation: accurately weigh the following raw materials by mass percentage: 2% to 4% sodium chloride, 1% to 2% urea, 0.2% to 0.4% sodium monofluorophosphate corrosion inhibitor, 0.5% to 1.1% γ-aminopropyltriethoxysilane, 2% to 4% carbon black nanoparticles, 2% to 3% expanded graphite, 2% to 3% methyltriethoxysilane, 3% to 5% ethanol phase solvent, 77.6% to 85.06% matrix aqueous solution; B. Mixed dissolution: first add the weighed sodium chloride and urea into the ethanol phase solvent and stir to disperse, then add the sodium monofluorophosphate corrosion inhibitor and mix well, then add γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite and methyltriethoxysilane in sequence and stir well; C. Subsequent treatment: Let the solution stand and observe, if there are impurities, filter them out to finally obtain a photothermal superphobic aqueous solution.

[0066] The prepared dynamic spraying device for the photothermal superhydrophobic aqueous solution on the bridge deck includes a bridge installation bracket 1, a spray head assembly 2, a solution delivery branch pipe 5, a solution delivery main pipe 7, a liquid storage tank 12, and a connection assembly 14. The curve shape of the bridge installation bracket 2 matches the curve shape of the bridge structure and is fixedly installed on the bridge auxiliary structure 4 through bolts 3. The liquid storage tank 12 is fixedly arranged under the bridge opening through a hanging bracket 10, and is internally provided with a liquid level sensor 11 and an anti-sediment stirring device 13. Both ends of the hanging bracket 10 are fixed on the bridge structure. The liquid level sensor 11 and the anti-sediment stirring device 13 are connected to the intelligent control system through wires. The connection assembly 14 uses a metal bellows or a flexible rubber joint, one end of which is fixed on the bridge installation bracket 1 and the other end is firmly connected to the liquid storage tank 12 to ensure the normal operation of the spraying device when the bridge deforms. The outlet of the liquid storage tank 12 is hermetically connected to the solution delivery main pipe 7 through an elbow 9. The solution delivery main pipe 7 is hermetically connected to the solution delivery branch pipe 5. The solution delivery branch pipe 5 is laid along the bridge direction and fixed on the bridge installation bracket through pipe clamps 6. A number of spray head assemblies 2 are evenly arranged on the solution delivery branch pipe 5. An intelligent flow regulating valve 8 is arranged on the solution delivery main pipe 7, and the intelligent flow regulating valve 8 is electrically connected to the intelligent control system.

[0067] The spray head assembly 2 includes a flow channel 201, a spiral guide vane 202, a dispersion plate 203, a reinforcing rib 204, a dispersion hole 205, a diffusion plate base 206, a diffusion plate 207, a radial guide groove 208, a tee 209, a spray head solution delivery pipe 210, an electric push rod 211, a ball hinge 212, a spray head installation bracket 213, and an installation bolt hole 214. The spray head solution delivery pipe 210 is hermetically connected to the solution delivery branch pipe 5. The three ports of the tee 209 are respectively connected to the inlet of the flow channel 201, the spray head solution delivery pipe 210, and one end of the electric push rod 211. A spiral guide vane 202 is welded inside the flow channel 201. A dispersion plate 203 is fixedly arranged at the end of the flow channel 201 far from the tee 209, and dispersion holes 205 are evenly arranged on the dispersion plate 203. The shape of the diffusion plate 207 is a detachable flared mouth, which is connected to the front end of the spray head through a thread, with a diffusion angle of 60°, and 6 radial guide grooves 208 are evenly arranged on the inner wall. One end of the electric push rod 211 is connected to the tee 209, and the other end is fixedly connected to the spray head installation bracket 213 through a ball hinge 212. The entire spray head assembly 2 is fixed on the bridge installation bracket 1 through bolts and installation bolt holes 214. The reinforcing rib 204 is a radial rib with a thickness of 3 mm, and 6 ribs are evenly distributed along the outer wall of the spray head and extend to the diffusion plate base 206 to enhance the structural strength of the spray head and prevent deformation caused by high-pressure spraying.

[0068] A stepper motor is provided inside the electric push rod 211. The stepper motor is connected to the intelligent control system through a waterproof cable, receives PWM signals to adjust the telescopic amount, thereby adjusting the angle of the nozzle, and achieving precise control of the spraying angle; the ball hinge 212 uses a stainless steel ball head in cooperation with a polytetrafluoroethylene bearing seat, allowing the nozzle to rotate horizontally by ±45° and vertically by ±30°, playing a role in connection and flexible rotation during the adjustment of the nozzle angle.

[0069] The spraying control method of the dynamic spraying device includes sensor data acquisition, data processing and analysis, feature construction and decision generation, remote monitoring and adaptive adjustment, and is characterized in that: The sensor data acquisition: Measure the bridge deck temperature value through a multi-point layout temperature sensor and calculate the temperature gradient, record the temperature historical data within 1 hour; use a humidity sensor to monitor the humidity of the bridge deck to assist in analyzing the icing risk; use a light intensity sensor to feedback the light intensity to evaluate the utilization degree of the photothermal effect; use an ice layer thickness sensor to measure the ice layer thickness of the bridge deck, and characterize the development of the ice layer through the thickness change rate; The data processing and analysis: First, collect the original data of various sensors and normalize them to the [0-1] interval by the linear method for convenient comprehensive operation and analysis; then adopt a moving average filtering algorithm to denoise the original data through a moving window with a length of 5 to ensure the accuracy of the data; The feature construction and decision generation: Include the construction of icing risk features, the estimation of photothermal effect features, the characterization of ice layer state features, and decision generation. Based on machine learning algorithms, the optimal spraying control strategy is generated through the construction of icing risk factors, photothermal effect features, and ice layer state features; The remote monitoring and adaptive adjustment: Include a remote monitoring function and an adaptive adjustment function; the remote monitoring function connects the device to the remote monitoring platform through a 4G / 5G network to view information such as the liquid level of the liquid storage tank, pipeline pressure, and nozzle angle, and remotely modify the spraying parameters and control the start and stop of the device; the adaptive adjustment function dynamically optimizes the spraying control strategy according to the weather and the icing conditions of the bridge, and adjusts parameters such as the spraying area and flow rate.

[0070] In the process of data processing and analysis, when collecting the original data of various sensors and normalizing them to the [0-1] interval by the linear method, the temperature uses the formula: Tnorm=(T - Tmin) / (Tmax - Tmin) (Tmin = -10 °C, Tmax = 5 °C) for linear mapping to [0-1]; the humidity is normalized by percentage value (0 - 100% corresponds to [0-1]); the light intensity is normalized according to the maximum sunshine intensity in the region; the moving average filtering algorithm is fixed at 5 data points with a time interval of 1 minute, smooths the noise through historical data, and uses the mirror filling method for the first and last data to avoid edge data distortion, reducing the noise by 70%.

[0071] During the feature construction and decision-making generation process, the icing risk feature construction determines the icing risk area through a specific calculation formula, that is, through the icing risk factor Frisk = humidity normalization value × (1 - |temperature normalization value - 0.5|), where 0°C corresponds to the normalization value of 0.5; the estimation of the photothermal effect feature estimates the expected photothermal temperature rise value Fphoto according to the light intensity and the photothermal efficiency curve to assist in the spraying decision; the characterization of the ice layer state feature calculates the ice layer thickness change rate Fice to judge the development of the ice layer; the decision-making generation includes threshold setting, spraying order decision-making, nozzle angle decision-making, flow rate decision-making, and spraying duration decision-making; among them, the threshold setting refers to setting the icing risk threshold Frisk, the photothermal effect threshold Fphoto, the ice layer thickening-related thresholds Tice1 and Tice2 (Tice1 < Tice2); the spraying order decision-making refers to determining the order according to the comparison between the feature indicators and the thresholds, and spraying the well-lit area first if the light is good and the icing risk is high, otherwise in the normal order; the nozzle angle decision-making refers to adjusting the nozzle towards the light direction if the light is good and aiming at the easily icing parts if the icing risk is high; the flow rate decision-making refers to adjusting the flow rate according to the ice layer thickness change rate, with a large rate for a large flow rate, a medium rate for a medium flow rate, and a small rate for a small flow rate; the spraying duration decision-making refers to determining the spraying duration according to the icing risk and the ice layer thickening situation, with a long duration for high risk and fast thickening, and a short duration otherwise.

[0072] During the feature construction and decision-making generation process, the spraying control strategy includes preventive basic spraying, targeted enhanced spraying, and regular maintenance spraying; preventive basic spraying is started when winter comes or the temperature drops but there is no ice formation, spraying from the high part to the low part of the bridge, from the center to both sides, with a moderate flow rate to form a uniform coating, using superhydrophobic and photothermal effects to prevent water from icing, increase the bridge deck temperature, and prevent icing; targeted enhanced spraying is triggered when the risk of the ice layer or the easily icing area increases, adjusting the nozzle angle to aim at the target, increasing the flow rate to accelerate melting, and increasing the spraying frequency according to the icing situation; based on the comprehensive bridge usage, environmental data, and the previous de-icing effect, regular maintenance spraying is carried out once a week, with a full or partial spraying, and adjusting the flow rate and duration according to the situation.

[0073] The icing risk threshold F risk : Initially set to 0.6, if the icing frequency > 20%, the threshold is lowered to 0.55; The photothermal effect threshold F photo : Set to 0.7 according to the light intensity and the solution photothermal conversion efficiency curve; The ice layer thickening threshold: T ice1 = 0.05 mm / min, which is mild icing and triggers basic spraying; T ice2 = 0.1 mm / min, which is severe icing and triggers enhanced spraying; The spraying sequence decision: If F risk ≥ 0.6 and F photo ≥ 0.7, give priority to spraying the areas with sufficient light, and utilize the photothermal effect to accelerate ice melting; If F risk ≥ 0.6 but there is insufficient light, spray according to the sorting of the ice layer thickness change rate; The nozzle angle decision: ±45° in the horizontal direction and ±30° in the vertical direction, and adjust it in real time through the PID algorithm to ensure coverage of the target area; The spraying flow rate decision: The basic flow rate is 5 L / min, and for every 0.01 mm / min increase in the ice layer thickening rate, the flow rate is increased by 10%; The spraying duration decision: Spraying duration = ice layer thickness / (flow rate × solution ice melting efficiency), where the ice melting efficiency is calibrated to 0.8 mm / L.

[0074] The specific embodiments of the present invention are as follows: I. Specific embodiments for the preparation of the bridge deck photothermal superhydrophobic aqueous solution: Embodiment

[0075] Accurately weigh each raw material according to the ratio of 4% sodium chloride, 2% urea, 0.4% sodium monofluorophosphate, 4% carbon black nanoparticles, 3% methyltriethoxysilane, 3% expanded graphite, 5% ethanol, 1% aminopropyltriethoxysilane (KH-550), and 77.6% water. First, add sodium chloride and urea to ethanol, and stir at 300 - 500 r / min at room temperature for 10 - 20 minutes to make them evenly dispersed; then add sodium monofluorophosphate and continue to stir for 5 - 10 minutes to mix evenly; then add KH-550, carbon black nanoparticles, expanded graphite, and MTES in sequence, and stir at 400 - 600 r / min for 15 - 30 minutes each time to promote the interaction, dispersion, and reaction among the components. Finally, let it stand for 30 - 60 minutes to observe the solution state. If there are abnormal situations such as impurities, filter it with a 0.2 - 0.5 μm filter screen to obtain the qualified bridge deck photothermal superhydrophobic aqueous solution. Embodiment

[0076] Accurately weigh each raw material according to the proportion of 2.7% sodium chloride, 1.3% urea, 0.27% sodium monofluorophosphate, 2.7% carbon black nanoparticles, 2% methyltriethoxysilane, 2% expanded graphite, 3.3% ethanol, 0.67% aminopropyltriethoxysilane (KH-550), and 85.06% water. First, add sodium chloride and urea to ethanol, and stir at 400 r / min for 15 minutes at room temperature to make them evenly dispersed; then add sodium monofluorophosphate and continue to stir for 8 minutes to mix evenly; then add KH-550, carbon black nanoparticles, expanded graphite, and MTES in sequence, and stir at 500 r / min for 20 minutes each time to promote the interaction, dispersion, and reaction among the components. Finally, let it stand for 45 minutes to observe the solution state. If there are abnormal situations such as impurities, filter it with a 0.3 μm filter screen to obtain a qualified bridge deck photothermal superhydrophobic aqueous solution.

[0077] II. Specific embodiments of the dynamic spraying device for the bridge deck photothermal superhydrophobic aqueous solution:

[0078] For customized bridge installation brackets, if the bridge is an arch bridge, according to the actual curve dimensions of the bottom and side surfaces of the arch bridge, use aluminum alloy materials to make a fitting bracket through machining or 3D printing. At the inspection hole reserved on the bridge or at the bottom of the anti-collision guardrail, firmly install the bracket with special fastening clamps and high-strength bolts. During the installation process, use a level and a theodolite to ensure that the horizontal and vertical deviations of the bracket are within ±0.5".

[0079] The connecting component is selected as a metal bellows. Because it has good flexibility and corrosion resistance, it can effectively cope with the expansion and contraction and vibration of the bridge, ensuring the stability and long-term use of the device. One end is tightly connected to the installation bracket by a flange connection method to ensure that the connection part can withstand at least 500 N of tensile force and 2 MPa of pressure. The other end is firmly and tightly connected to the inlet end of the liquid storage tank by a clamp, and a sealing test is carried out after connection. When the pressure is maintained at 1.5 MPa, the leakage rate is lower than 0.1%.

[0080] When the liquid storage tank is prefabricated in the factory, interfaces for installing hanging brackets and brackets are reserved. After selecting a suitable position under the bridge, fix the hanging brackets and brackets to the bridge structure by bolt connection, and then install the liquid storage tank on it. Adjust the position to ensure that the horizontal deviation of the liquid storage tank is within ±0.3°. Then connect the lines of the liquid level sensor and the anti-sediment stirring device to the corresponding interfaces of the intelligent control system, and conduct a line test to ensure normal data transmission.

[0081] The conveying pipeline starts from the outlet of the liquid storage tank and is laid along the edge structure frame of the bridge. It is fixed with pipe clamps every 1.5 meters. At the pipe bends, 90° or 45° elbows are used for connection. At the connection with the nozzle, a tee with good sealing performance is used. After connection, a pressure test is carried out. There is no leakage under a pressure of 1 MPa. Then, the intelligent flow regulating valve is installed on the pipeline 2 - 3 meters away from the outlet of the liquid storage tank and is electrically connected to the intelligent control system for flow control calibration.

[0082] The nozzle assembly is fixed on the bridge structure through a stainless - steel nozzle mounting bracket. The bracket is connected by welding or bolts to ensure firm installation. The conveying pipe of the nozzle is connected to the solution conveying pipeline through a tee with good sealing performance to ensure that the solution is transported from the liquid storage tank to the nozzle without leakage through the intelligent flow valve. One end of the electric push rod is connected to the nozzle, and the other end is fixed to the mounting bracket through a ball joint for adjusting the angle of the nozzle. A stepping motor is built into the push rod and is connected to the intelligent control system through a waterproof cable. It receives PWM signals to adjust the telescopic amount and thus adjust the angle of the nozzle, realizing the horizontal ±45° and vertical ±30° angle adjustment of the nozzle and ensuring that there are no loosening, displacement, etc. during the spraying process. And an angle adjustment test is carried out to ensure that the adjustment accuracy is within ±2°. The ball joint plays a role of connection and flexible rotation during the angle adjustment of the nozzle.

[0083] III. Specific embodiments of the spraying control method:

[0084] 1. Layout and installation of sensors: The temperature sensor has an accuracy of up to ±0.5°C to ensure the accuracy of the collected data. A PT100 platinum resistance sensor (±0.5°C) is used. It is embedded every 5 meters on the shaded side, installed every 10 meters on the bridge edge, and evenly distributed every 15 meters in the center of the bridge deck. It is calibrated once a year.

[0085] The humidity sensor has an accuracy of up to ±3% RH to ensure the accuracy of the collected data. A capacitive sensor (±3% RH) is used. It is mounted every 5 meters at the drainage outlet and expansion joint, installed every 10 meters in the condensation area, and the probe is exposed to prevent condensation.

[0086] The light intensity sensor has an accuracy of up to ±10 W / m² to ensure the accuracy of the collected data. One is fixed every 20 meters on the top of the guardrails on both sides of the bridge deck through a bracket, and the sensor is tilted upwards by 30°. Two are installed on the top of the bridge (near the main tower of this cable - stayed bridge) for monitoring the overall light intensity.

[0087] The ice layer thickness sensor has an accuracy of ±0.5 mm to ensure the accuracy of the collected data. The probe is vertically embedded 3 - 5 cm into the bridge deck, the bottom is in contact with the bridge deck, and the surrounding is sealed with silicone to prevent water vapor intrusion. It is compared with manual measurement through ultrasonic echo signals every day. When the error exceeds ±0.5 mm, the system alarm is triggered.

[0088] 2. Data acquisition and processing: The collected data is processed by the microprocessor built into the intelligent control system. The original data is normalized using the min-max normalization method, and then sliding average filtering with a window length of 5 is used to remove noise. For example, when the temperature data range is -10°C to 5°C, if the collected temperature is 0°C, the normalized value is (0 - (-10)) / (5 - (-10)) = 2 / 3. Assume that the set icing risk threshold F risk = 0.6, the photothermal effect threshold F photo = 0.7, the ice layer thickening threshold T ice1 = 0.05 mm / min and T ice2 = 0.1 mm / min. When the calculated icing risk factor F risk = 0.7 for a certain area and the light intensity meets the photothermal effect condition, spraying is preferentially carried out on this area; if the ice layer thickness change rate F ice = 0.12 mm / min, the intelligent flow regulating valve will increase the flow by 50%, adjust the nozzle angle to the direction with the fastest ice layer thickening, and extend the spraying duration by 30%.

[0089] 3. Specific application examples: Specific application example 1 (new spraying control scenario) Scenario: Rapid icing after heavy rain Trigger conditions: Humidity > 90%, temperature drops suddenly to -3°C, ice layer thickening rate > 0.1 mm / min.

[0090] Spraying strategy: Increase the flow to 7.5 L / min, and aim the nozzle at the low-lying water accumulation area; Extend the spraying duration to 15 minutes and start secondary spraying (with an interval of 5 minutes).

[0091] Experimental data support: Photothermal heating effect: The bridge deck temperature rises by 3 - 5°C under 500 W / m² light irradiation for a solution containing 4% carbon black (measured data); Inhibitor efficiency: 0.4% sodium monofluorophosphate reduces the steel corrosion rate by 85% (ASTM G31 test).

[0092] Specific application example 2 (continuous low temperature and multi-sunshine scenario) Threshold adjustment: When the light intensity continuously > 800 W / m², the photothermal effect threshold F photo drops to 0.6; Spraying strategy: Tilt the nozzle angle 30° towards the light direction, reduce the flow by 20%, and use the photothermal effect to extend the ice inhibition duration.

[0093] In actual operation, when winter comes and the temperature continues to drop but there is no ice formation yet, start the preventive basic spraying procedure. At this time, spray the solution at a moderate flow rate in the established order from the high to the low part of the bridge and from the center to both sides. During the spraying process, ensure that the nozzle angle is stable and the coverage is uniform, so that a thin and uniform photothermal superhydrophobic coating can be formed on the bridge surface. This coating can utilize its superhydrophobic property to quickly slide off the rainwater, snowmelt, etc. that land on the bridge surface, effectively reducing the formation of ponding. At the same time, with the photothermal effect, it absorbs and converts light energy into heat energy when irradiated by sunlight, increasing the temperature of the bridge surface, thus preventing the occurrence of icing in advance and laying a good foundation for the safe passage of the bridge surface throughout the cold season.

[0094] When the ice thickness sensor detects local thin ice on the bridge surface, or when it is judged through comprehensive data such as temperature and humidity that the icing risk in specific easily icing areas (such as shaded areas, windward areas, etc.) increases significantly, the intelligent control system will immediately trigger targeted enhanced spraying operations to ensure timely response to the icing risk. First, quickly adjust the nozzle angle through the electric push rod to accurately aim at the ice layer and the surrounding easily icing parts, ensuring that the photothermal superhydrophobic solution can fully cover the target area. At the same time, appropriately increase the setting of the intelligent flow regulating valve to increase the spraying flow rate, so that more solution acts on the ice layer and the surrounding area, accelerating the melting of the ice layer and enhancing the photothermal superhydrophobic property of this area. During the spraying process, continuously monitor the melting situation of the ice layer and the icing risk. If it is found that the ice layer melts slowly or there is a sign of re-icing after melting, then spray this area multiple times within a short period according to the actual situation, dynamically increasing the spraying frequency, and continuously ensuring that this area has good ice inhibition and de-icing capabilities and maintaining its photothermal superhydrophobic property at a relatively high level.

[0095] During the entire winter or the easily icing season, it is necessary to comprehensively consider the actual usage situation of the bridge (such as the traffic volume, vehicle types, etc.), environmental monitoring data (such as the temperature change range, snowfall frequency, wind speed, etc.) and the feedback of the previous spraying effect (such as the decline rate of the photothermal superhydrophobic property in some areas, whether there is local ponding or icing, etc.) to determine the period of regular maintenance spraying. Generally, a full or partial spraying can be carried out every week, but it also needs to be adjusted flexibly according to the actual icing situation. When carrying out spraying maintenance, if it is found that the overall photothermal superhydrophobic property of the bridge surface is maintained well and only there are individual slightly worn or performance-declining areas, then key spraying maintenance can be carried out for these areas, appropriately adjusting the spraying flow rate and duration to supplement the coating lost due to factors such as vehicle driving and natural environment erosion, and ensuring that each part can continuously play a good ice inhibition and de-icing effect; if there is a trend of slow thickening of the ice layer and a thin coating in some areas of the bridge surface, the flow rate can be appropriately increased and the spraying duration can be extended; if the overall condition of the bridge surface is good and the coating still maintains good integrity and performance, then spraying can be carried out according to the conventional flow rate and duration to achieve the rational use of resources and the optimization of the spraying effect.

[0096] Through the synergistic effect of the innovative design of the above-mentioned preparation of the photothermal superhydrophobic aqueous solution for the bridge deck, the dynamic spraying device, and the spraying control strategy, the present invention can effectively solve the problems that the bridge deck is prone to icing in winter and it is difficult to deice, reduce the damage to the bridge structure caused by icing, improve the safety and traffic capacity of the bridge deck under low-temperature ice and snow weather, and has significant practical value and social benefits.

[0097] The above shows and describes the basic principles, main features, and innovative advantages of the present invention. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description, and all changes made within the scope of the claims are encompassed within the protection scope of the present invention.

Claims

1. A bridge deck photothermal superhydrophobic aqueous solution, characterized in that: The bridge deck photothermal super-phobic solution is composed of traditional ice-melting components, corrosion inhibitors, photothermal hydrophobic materials, a phase solvent and a matrix; the traditional ice-melting components include sodium chloride and urea, the mass percentage of sodium chloride is 2% to 4%, and the mass percentage of urea is 1% to 2%; the corrosion inhibitor is sodium monofluorophosphate, and the mass percentage is 0.2% to 0.4%; the photothermal hydrophobic material is composited by γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite, and methyltriethoxysilane, wherein the mass percentage of γ-aminopropyltriethoxysilane is 0.5% to 1.1%, the mass percentage of carbon black nanoparticles is 2% to 4%, the mass percentage of expanded graphite is 2% to 3%, and the mass percentage of methyltriethoxysilane is 2% to 3%; the phase solvent is ethanol, and the mass percentage is 3% to 5%; the matrix is ​​water, and the mass percentage of water is 77.6% to 85.06%.

2. The method for preparing the bridge deck photothermal super-hydrophobic solution according to claim 1 comprises the following specific steps: A. Raw material preparation: accurately weigh the following raw materials by mass percentage: 2% to 4% sodium chloride, 1% to 2% urea, 0.2% to 0.4% sodium monofluorophosphate corrosion inhibitor, 0.5% to 1.1% γ-aminopropyltriethoxysilane, 2% to 4% carbon black nanoparticles, 2% to 3% expanded graphite, 2% to 3% methyltriethoxysilane, 3% to 5% ethanol phase solvent, 77.6% to 85.06% matrix aqueous solution; B. Mixed dissolution: first add the weighed sodium chloride and urea into the ethanol phase solvent and stir to disperse, then add the sodium monofluorophosphate corrosion inhibitor and mix well, then add γ-aminopropyltriethoxysilane, carbon black nanoparticles, expanded graphite and methyltriethoxysilane in sequence and stir well; C. Subsequent treatment: Let the solution stand and observe, if there are impurities, filter them out to finally obtain a photothermal superphobic aqueous solution.

3. The dynamic spraying device for the light-heat superhydrophobic aqueous solution on the bridge deck prepared according to claim 2, characterized in that: The dynamic spraying device includes a bridge installation bracket (1), a nozzle assembly (2), a solution delivery branch pipe (5), a solution delivery main pipe (7), a liquid storage tank (12) and a connection assembly (14). The curve shape of the bridge installation bracket (1) matches the curve shape of the bridge structure and is fixedly installed on the bridge auxiliary structure (4) through bolts (3). The liquid storage tank (12) is fixedly arranged under the bridge opening through a hanger (10) and is internally provided with a liquid level sensor (11) and an anti-precipitation stirring device (13). Both ends of the hanger (10) are fixed on the bridge structure. The liquid level sensor (11) and the anti-precipitation stirring device (13) are connected to the intelligent control system through wires. The connection assembly (14) adopts a metal bellows or a flexible rubber joint, one end of which is fixed on the bridge installation bracket (1) and the other end is firmly connected to the liquid storage tank (12) to ensure the normal operation of the spraying device when the bridge deforms. The outlet of the liquid storage tank (12) is hermetically connected to the solution delivery main pipe (7) through an elbow (9). The solution delivery main pipe (7) is hermetically connected to the solution delivery branch pipe (5). The solution delivery branch pipe (5) is laid along the bridge direction and is fixed on the bridge installation bracket (1) through pipe clamps (6). A number of nozzle assemblies (2) are evenly arranged on the solution delivery branch pipe (5). An intelligent flow regulating valve (8) is arranged on the solution delivery main pipe (7), and the intelligent flow regulating valve (8) is electrically connected to the intelligent control system.

4. The dynamic spraying device for the bridge deck light-heat superhydrophobic aqueous solution according to claim 3, wherein: The nozzle assembly (2) includes a flow channel (201), a spiral guide vane (202), a dispersion plate (203), a reinforcing rib (204), a dispersion hole (205), a diffuser base (206), a diffuser (207), a radial guide groove (208), a tee (209), a nozzle solution delivery pipe (210), an electric push rod (211), a ball hinge (212), a nozzle mounting bracket (213) and a mounting bolt hole (214). The nozzle solution delivery pipe (210) is hermetically connected to the solution delivery branch pipe (5); three ports of the tee (209) are respectively connected to the inlet of the flow channel (201), the nozzle solution delivery pipe (210) and one end of the electric push rod (211). The spiral guide vane (202) is welded inside the flow channel (201). A dispersion plate (203) is fixedly arranged at the end of the flow channel (201) far from the tee (209). Dispersion holes (205) are uniformly arranged on the dispersion plate (203); the diffuser (207) is in the shape of a detachable flared opening, is connected to the front end of the nozzle by threads, has a diffusion angle of 60°, and 6 radial guide grooves (208) are uniformly arranged on the inner wall; one end of the electric push rod (211) is connected to the tee (209), and the other end is fixedly connected to the nozzle mounting bracket (213) through the ball hinge (212). The entire nozzle assembly (2) is fixed on the bridge mounting bracket (1) through bolts and the mounting bolt holes (214); the reinforcing rib (204) is a radial rib with a thickness of 3 mm, 6 are uniformly distributed along the outer wall of the nozzle and extend to the diffuser base (206) to enhance the structural strength of the nozzle and prevent deformation caused by high-pressure spraying.

5. The dynamic spraying device for the light-heat superhydrophobic aqueous solution on the bridge deck according to claim 4, characterized in that: A stepping motor is arranged inside the electric push rod (211). The stepping motor is connected to the intelligent control system through a waterproof cable, receives a PWM signal to adjust the telescopic amount so as to adjust the angle of the nozzle, and realizes precise control of the spraying angle. The ball hinge (212) uses a stainless steel ball head in cooperation with a polytetrafluoroethylene bearing seat, allowing the nozzle to rotate horizontally by ±45° and vertically by ±30°, and playing a role of connection and flexible rotation during the process of adjusting the angle of the nozzle.

6. The spraying control method of the dynamic spraying device according to any one of claims 3 to 5, including sensor data acquisition, data processing and analysis, feature construction and decision generation, remote monitoring and adaptive adjustment, characterized in that: The sensor data acquisition: Measuring the bridge deck temperature value through a multi-point layout temperature sensor and calculating the temperature gradient, and recording the temperature historical data within 1 hour; Monitoring the humidity of the bridge deck by distributing humidity sensors to assist in analyzing the icing risk; Using a light intensity sensor to feedback the light intensity to evaluate the utilization degree of the photothermal effect; Measuring the ice layer thickness on the bridge deck by using an ice layer thickness sensor, and characterizing the development of the ice layer through the thickness change rate; The data processing and analysis: First, collect the raw data of various sensors and normalize it to the range of [0-1] using the linear method for convenient comprehensive operation and analysis. Then, adopt the moving average filtering algorithm to denoise the raw data through a moving window with a length of 5 to ensure the accuracy of the data. The feature construction and decision generation: It includes ice formation risk feature construction, photothermal effect feature estimation, ice layer state feature characterization, and decision generation. Based on machine learning algorithms, through the construction of ice formation risk factors, photothermal effect features, and ice layer state features, an optimal spraying control strategy is generated. The remote monitoring and adaptive adjustment: It includes a remote monitoring function and an adaptive adjustment function. The remote monitoring function connects the device to the remote monitoring platform through a 4G / 5G network to view information such as the liquid storage tank liquid level, pipeline pressure, and nozzle angle, and remotely modify the spraying parameters and control the start and stop of the device. The adaptive adjustment function dynamically optimizes the spraying control strategy according to the weather and bridge icing conditions, and adjusts parameters such as the spraying area and flow rate.

7. The spraying control method according to claim 6, wherein: In the process of data processing and analysis, when collecting the raw data of various sensors and normalizing it to the range of [0-1] using the linear method, for temperature, the formula is: Tnorm=(T-Tmin) / (Tmax-Tmin); for humidity, it is normalized using percentage values, where 0-100% corresponds to [0-1]; for light intensity, it is normalized according to the maximum sunshine intensity in the region. The moving average filtering algorithm is fixed at 5 data points with a time interval of 1 minute. It smooths the noise through historical data, and the head and tail data are filled using the mirror filling method to avoid edge data distortion, and the noise is reduced by 70%.

8. The spraying control method according to claim 6, wherein: In the process of feature construction and decision generation, the ice formation risk feature construction is determined through a specific calculation formula, that is, the ice formation risk factor Frisk = normalized humidity value × (1 -|normalized temperature value - 0.5|) is used to determine the ice formation risk area, where 0°C corresponds to a normalized value of 0.

5. The photothermal effect feature estimation estimates the expected photothermal temperature rise value Fphoto according to the light intensity and the photothermal efficiency curve to assist in the spraying decision. The ice layer state feature characterization calculates the ice layer thickness change rate Fice to judge the development of the ice layer. The decision generation includes threshold setting, spraying order decision, nozzle angle decision, flow rate decision, and spraying duration decision. Among them, the threshold setting refers to setting the ice formation risk threshold Frisk, the photothermal effect threshold Fphoto, and the ice layer thickening related thresholds Tice1 and Tice2, where Tice1 < Tice2. The spraying order decision refers to determining the order by comparing the feature indicators with the thresholds. Spraying the well-lit area with high ice formation risk is prioritized when the light is good, otherwise in the normal order. The nozzle angle decision refers to adjusting the nozzle angle towards the light direction when the light is good and aiming at the easily iced parts when the ice formation risk is high. The flow rate decision refers to adjusting the flow rate according to the ice layer thickness change rate, with a large rate corresponding to a large flow rate, a medium rate corresponding to a medium flow rate, and a small rate corresponding to a small flow rate. The spraying duration decision refers to determining the spraying duration according to the ice formation risk and the ice layer thickening situation, with a long duration for high risk and rapid thickening, and a short duration otherwise.

9. The spraying control method according to claim 6, wherein: During the feature construction and decision-making generation process, the spraying control strategy includes preventive basic spraying, targeted enhanced spraying, and regular maintenance spraying; preventive basic spraying is initiated when winter is approaching or the temperature drops but does not freeze, spraying from the high part to the low part of the bridge, from the center to both sides, with a moderate flow rate to form a uniform coating, using the superhydrophobic and photothermal effects to prevent water from freezing, increase the bridge deck temperature, and prevent icing; targeted enhanced spraying is triggered when the risk of ice layer or easily icing area increases, adjusting the nozzle angle to aim at the target, increasing the flow rate to accelerate melting, and increasing the spraying frequency according to the icing situation; based on the bridge usage, environmental data, and previous deicing effects, regular maintenance spraying is carried out once a week, with full or partial spraying, and the flow rate and duration are adjusted according to the situation.

10. The spraying control method according to claim 8, wherein: The icing risk threshold F risk : Initially set to 0.

6. If the icing frequency > 20%, the threshold is lowered to 0.55; The photothermal effect threshold F photo : Set to 0.7 according to the curve of light intensity and solution photothermal conversion efficiency; The ice layer thickening threshold: T ice1 = 0.05 mm / min, for slight icing, triggering basic spraying; T ice2 = 0.1 mm / min, for severe icing, triggering enhanced spraying; The spraying sequence decision: If F risk ≥ 0.6 and F photo ≥ 0.7, give priority to spraying the areas with sufficient sunlight, and use the photothermal effect to accelerate ice melting; If F risk ≥ 0.6 but there is insufficient sunlight, spray according to the sorting of the ice layer thickness change rate; The decision of the nozzle angle: ±45° in the horizontal direction and ±30° in the vertical direction, which is adjusted in real time through the PID algorithm to ensure coverage of the target area; The decision of the spraying flow rate: the basic flow rate is 5 L / min, and for every 0.01 mm / min increase in the ice layer thickening rate, the flow rate is increased by 10%; The decision of the spraying duration: spraying duration = ice layer thickness / (flow rate × solution ice melting efficiency), where the ice melting efficiency is calibrated to 0.8 mm / L.

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