Second-order epoxy bonding oil for road and bridge pavement as well as preparation and use methods of second-order epoxy bonding oil

Abstract

The invention belongs to the field of road and bridge pavement materials, and particularly relates to second-order epoxy bonding oil for road and bridge pavement, which comprises a main agent A and a curing agent B. The main agent A comprises epoxy resin, a flexibilizer, a waterproof agent and a diluent, and the curing agent B comprises a normal-temperature curing agent, a latent curing agent and an accelerant. The ratio of all components in the main agent A and the curing agent B is adjusted according to actual paving information; the adjusting mode of the proportion comprises the steps that an associated data model about historical paving information, historical environment information and historical bonding oil formula information is established, and the paving information comprises paving base information, paving upper layer information and construction information; the environment information comprises temperature, humidity and wind speed; actual paving information and environment information are sequentially obtained in production; and inputting the data into the associated data model, and outputting a recommended bonding oil formula.

Description

Technical Field

[0001] The present invention relates to the technical field of road and bridge paving materials, and in particular to a second-stage epoxy adhesive oil for road and bridge paving, and a preparation method and a use method thereof. Background Art

[0002] The waterproof bond coat in road and bridge pavement performs multiple functions during construction: waterproofing, bonding, and stress transfer. It prevents moisture from penetrating the base layer, preventing corrosion and aging, and improves the interfacial adhesion between the base and upper pavement layers, preventing delamination. Furthermore, under load, the bond coat evenly transfers stress through the interface, preventing crack propagation. However, with increasing traffic loads and increasingly complex environmental conditions, problems with traditional road and bridge pavement materials and processes have gradually become apparent. For example, two persistent challenges with the (waterproof) bond coat in road and bridge pavement, such as steel bridge decks, concrete bridge decks, and tunnel pavements, are how to improve the bond between the (waterproof) bond coat and the upper pavement layer, and how to minimize damage to the (waterproof) bond coat caused by pavers, material transporters, and other equipment during construction.

[0003] The solutions to these two problems are often contradictory: increasing the bonding performance often requires that the (waterproof) bonding layer remain in an uncured state during the construction of the upper pavement, but the sticking of the construction machinery will destroy the integrity of the (waterproof) bonding layer; and when the (waterproof) bonding layer is completely cured, although the problem of construction machinery sticking is solved, the bonding performance between the cured (waterproof) bonding layer and the upper pavement is almost lost.

[0004] The means to solve this problem in the industry have gone through the following processes: using a thermoplastic asphalt bonding layer, using a thermosetting epoxy asphalt bonding layer, using a multi-layer acrylic waterproof bonding layer, and using a second-stage epoxy bonding oil.

[0005] Currently, a second-stage epoxy bond coat is the most commonly used design. Epoxy bond oils are widely used as waterproof bond coats for steel and concrete bridge decks due to their excellent bond strength, waterproof properties, and durability. However, existing epoxy bond oils still face numerous challenges in practical applications, particularly significant performance fluctuations under varying environmental conditions. This further limits the reliability and universality of second-stage epoxy bond oils in road and bridge pavement applications.

[0006] Specifically, in the first stage of curing, the bonding layer needs to be quickly cured to a "non-stick wheel" state to avoid mechanical damage from the paver and material transporter. However, curing too quickly may cause the bonding performance of the bonding layer to the upper paving material to decrease. In the second stage of curing, the latent curing agent needs to be stimulated by construction heat or the external environment after the upper paving is installed to complete deep curing. However, under different construction environments, it is difficult to accurately control the degree of heat stimulation and curing time, resulting in unstable performance of the bonding layer. This is typically manifested in high temperature environments. If the curing speed is too fast, the bonding layer may not be fully integrated into the upper paving, resulting in a decrease in bonding performance. In low temperature or high humidity environments, the curing reaction is inhibited, which prolongs the construction time and even affects the final bonding strength.

[0007] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0008] The first purpose of the present invention is to provide a second-stage epoxy adhesive for road and bridge paving. Through innovative data processing algorithms and formula optimization models, the environmental adaptability, construction convenience and performance stability of the adhesive are significantly improved, and it can be widely used in steel bridge decks, concrete bridge decks and other road and bridge paving fields.

[0009] The above technical objectives of the present invention are achieved through the following technical solutions: A second-stage epoxy adhesive for road and bridge paving, comprising a main agent A and a curing agent B. The main agent A comprises an epoxy resin, a toughening agent, a waterproofing agent, and a diluent, and the curing agent B comprises a room-temperature curing agent, a latent curing agent, and an accelerator. The ratio of the components in the main agent A and the curing agent B is adjusted based on actual paving information. In the present invention, the curing of the second-stage epoxy adhesive oil is mainly divided into two stages: the first stage is room temperature curing: at this time, the epoxy resin in the main agent A and the room temperature curing agent in the curing agent B undergo a ring-opening polymerization reaction to form a preliminary cross-linked network, ensuring that the adhesive oil has adhesion and preliminary strength, and at the same time has a certain thermoplasticity, which can adapt to mechanical loads during construction; the second stage is high-temperature curing: specifically under high-temperature paving of asphalt concrete, the epoxy resin in the main agent A and the latent curing agent in the curing agent B react under high-temperature activation to further form a denser cross-linked network, significantly improving the mechanical strength, durability and waterproof performance of the adhesive oil, and at the same time transforming it into an irreversible thermosetting structure.

[0010] The adjustment method of the ratio includes the following steps: S1 establishes a linked data model of historical paving information, historical environmental information, and historical bonding oil formula information. Paving information includes paving base information, paving upper layer information, and construction information; environmental information includes temperature, humidity, and wind speed. During actual paving, S2 obtains paving base information, paving upper layer information and construction information according to the construction plan, and summarizes them to form an actual paving data set; S3 obtains environmental information during the working hours of the construction day, assigns weights to each parameter based on its sensitivity to the performance of the adhesive oil, and makes corrections based on the fluctuation range of each parameter to construct a predicted environmental data set; S4 inputs the actual paving data set and the predicted environment data set into the associated data model and outputs the recommended bonding oil formula on the construction day.

[0011] Preferably, the epoxy resin in main agent A is one or more of bisphenol A epoxy resins E51, E44, E39, E20, and E12. Preferably, the epoxy resin has a molecular weight of 700-1200 g / mol and a viscosity of 0.01-0.05 Pa·s (25°C). It provides bonding strength and hardness, ensuring the adhesive oil forms a strong structure after curing. Its epoxy groups provide reactivity, allowing it to cross-link with the curing agent. The main agent A dosage accounts for 60%-80% of the total mass of main agent A. The network structure formed by the cured bisphenol A epoxy resin exhibits excellent mechanical properties, including high tensile strength, compressive strength, and shear resistance. This provides high-strength support, withstands the intense pressure of heavy traffic in road and bridge pavements, extends the service life of road and bridge pavement materials, and reduces damage caused by material fatigue or delamination.

[0012] The toughening agent is one or more of an organosilicon toughening agent, a polyether toughening agent or a liquid rubber toughening agent; Silicone toughening agents are flexible molecules containing a silicon-oxygen chain structure. The flexibility of the silicon-oxygen chain (-Si-O-Si-) enables it to improve toughness in the cured epoxy system, providing water resistance and high and low temperature resistance. Polyether toughening agents use polyethylene oxide (EO) or polypropylene oxide (PO) as the main chain segments, have a low glass transition temperature (Tg) and excellent flexibility, and enhance low-temperature toughness and fluidity. Liquid rubber toughening agents (such as CTBN and ATBN) are a type of low-molecular-weight rubber containing active end groups. They usually cross-link with epoxy resin through chemical reactions to form a block or dispersed phase structure. The rubber phase is dispersed in the cured epoxy matrix to form "micro-area toughening", which can significantly improve impact resistance and fatigue resistance.

[0013] Depending on the specific construction environment and requirements, the combination of toughening agents can achieve targeted optimization: in cold and high-altitude areas, polyether toughening agents are preferred, supplemented by liquid rubber; in high-humidity environments, silicone toughening agents are primarily used to enhance water resistance; in heavy traffic areas, liquid rubber toughening agents are primarily used, supplemented by polyether toughening agents to improve fatigue resistance. The preferred toughening agent dosage range is 5% to 15% of the total weight of the main agent A.

[0014] The waterproofing agent is one or more of the following: silane coupling agents A-151, A-172, KH-540, KH-560, KH-570, KH-602, and KH-791. The bifunctional structure of the silane coupling agent, where one end reacts with the epoxy resin and the other chemically bonds to the substrate surface, enhances the bond strength between the adhesive and the substrate. The silane coupling agent improves the wettability of the substrate surface, reduces the contact angle, and improves the adhesion of the epoxy adhesive. The interfacial layer it forms resists moisture penetration, enhancing waterproofing and interfacial stability. The dosage is 2%-5% of the total weight of the main agent A.

[0015] The diluent is one or more of butyl glycidyl ether, phenyl glycidyl ether, alkyl glycidyl ether, and carbonate diluents. These diluents can adjust the viscosity and workability of the adhesive oil while ensuring compatibility with the epoxy system and participation or volatilization during the curing process. The usage level should be 5%-15% of the total mass of the main agent A. The active epoxy groups contained in butyl glycidyl ether, phenyl glycidyl ether, and alkyl glycidyl ether can participate in the curing reaction, enhancing the strength and toughness of the system. Carbonate diluents such as propylene glycol carbonate (PC) and ethylene glycol carbonate (EGC) have lower viscosity than glycidyl ethers, significantly improving workability.

[0016] Preferably, in curing agent B, the room temperature curing agent includes one or more of polyamide curing agent, polyetheramine curing agent or fatty amine curing agent, the latent curing agent includes one or more of imidazole curing agent or dicyandiamide curing agent; the accelerator is imidazole or tertiary amine. Specifically, the room temperature curing agent provides rapid initial bonding, and the latent curing agent provides final strength at high temperature. Among them, the ratio of room temperature curing agent and latent curing agent is controlled in the range of 3:1~5:1 to balance the rapid curing and high temperature curing effects. Imidazole curing agent acts as a high temperature fast starter, and dicyandiamide releases active amines at high temperature to react with epoxy resin to form a high-strength cross-linked network. Accelerators can accelerate the reaction of room temperature curing agent or latent curing agent, shorten the curing time or adjust the reaction rate, especially under low temperature or tight construction time conditions. The dosage is usually 1%~5% of curing agent B. Preferably, the accelerator is one or more of 2-methylimidazole, 2-ethylimidazole, triethylamine, and triisopropylamine.

[0017] Preferably, the mass ratio of the main agent A to the curing agent B is 2 to 4:1. Specifically, the ratio is adjusted according to the environment. In high-temperature construction environments, the diluent is reduced and the proportion of the latent curing agent is increased. In low-temperature environments, the ratio of the diluent to the room-temperature curing agent is increased to accelerate the curing speed. In high-humidity environments, the proportion of the waterproofing agent is increased while the amount of the latent curing agent is reduced to avoid performance degradation caused by excessive curing time. By dynamically adjusting the formula, the present invention can generate the optimal adhesive oil formula based on the actual construction conditions of the day, thereby improving construction quality and efficiency.

[0018] Preferably, in step S1, the purpose is to build a correlation data model that can predict the bonding oil formula by analyzing historical paving data, environmental data and bonding oil formula performance, so as to provide a dynamic adjustment basis for actual construction. S11 collects historical paving information, historical environmental information, and historical adhesive oil formula information data, and pre-processes the collected historical data; Specifically, in order to obtain high-quality data, we can first determine the source of historical data, including sensor records, construction records, laboratory records, etc. After collecting historical data, we can perform data cleaning, check whether the data has missing values or outliers, and convert categorical variables into numerical variables. For data that cannot be directly expressed numerically, each information item is converted into a numerical feature. For example, the substrate type can be encoded as: steel bridge deck = 1, concrete bridge deck = 2, so that the data is at the same order of magnitude, avoiding the impact of data features on model training due to different orders of magnitude.

[0019] S12 converts the pre-processed historical data into feature vectors, and constructs a feature matrix based on the feature vectors; S13: calculating a correlation matrix based on the feature matrix, optimizing the feature matrix using the correlation matrix, and standardizing the optimized feature matrix to form a historical data set; On the basis of the above embodiment, each historical data record is converted into a row of feature vectors, and all features are combined into a matrix, where each row corresponds to a sample and each column corresponds to a feature; after the data is converted into a matrix, the correlation matrix can be calculated using matrix operations such as NumPy to analyze the redundancy between data features, the contribution of features to the target, etc., to facilitate the subsequent optimization of the feature matrix. The correlation matrix can help select model input variables, including deleting highly redundant features; for features with nonlinear relationships, the introduction of polynomial features or other transformations can be considered. In order to obtain high-quality data, it is also necessary to standardize or normalize the optimized feature matrix, convert the features into zero-mean, unit variance distributions, and scale them to a uniform range to avoid the dominance of model optimization due to excessively large values in the subsequent model training process.

[0020] S14 selects a suitable neural network model to construct a correlation data model, and uses the historical data set to train and optimize the correlation data model.

[0021] Specifically, the model selection process involves selecting an appropriate neural network model based on the data size and task characteristics, designing the input, hidden, and output layers for the selected model, and configuring the activation and loss functions. For model training and optimization, the historical dataset can be split into a training set and a test set. The model is trained using the training set, and the accuracy of the model is verified using the test set, ultimately resulting in a correlation data model that meets the accuracy requirements.

[0022] Preferably, in step S2, the purpose is to obtain real-time data from actual construction, including paving base, upper layer materials and construction parameters, to form a comprehensive data set to provide accurate input for subsequent binder oil formulation recommendations, wherein: Pavement base information includes base type and corresponding surface condition; base type includes steel bridge deck or concrete bridge deck, and surface condition includes roughness, moisture content and porosity; pavement base is one of the key factors in determining the selection of bonding oil formula. The base material type, condition and treatment method directly affect the bonding strength, toughness and waterproof performance of the bonding oil.

[0023] Information about the upper pavement layer includes asphalt concrete type, paving equipment, paving thickness, and paving temperature. The material and construction process of the upper pavement layer determine the thickness, curing speed, and bonding performance of the binder. Asphalt concrete types include densely graded asphalt (AC), stone aggregate asphalt (SMA), and open-graded drained asphalt (OGFC). Different asphalt mixtures have different paving temperature requirements, and the thickness of the upper pavement layer directly affects the choice and dosage of the binder.

[0024] Application information includes coating method and coating thickness.

[0025] The specific steps include: Based on the collection of paving base, upper layer and construction information, a complete set of actual paving data is formed; data collection can be carried out using tools such as infrared thermometers, laser level meters, sensors and GPS; at the construction site, a construction data collection system is used to directly upload data to the cloud database; Store the above data in a tabular or structured form to facilitate subsequent model input; Check whether the data is complete, for example, whether the base moisture content, upper layer thickness, etc. are missing. If some data is difficult to obtain in real time, empirical values or historical data can be introduced to supplement it; Then check whether there are any abnormal values (such as substrate temperature below 0°C, paving temperature below the required paving range), and ensure that the units and ranges of each parameter are consistent (such as temperature is unified in °C, speed is unified in m / min); Finally, it is organized into a standardized data structure for use in subsequent steps.

[0026] Preferably, in step S3, environmental information of the working hours on the construction day is obtained, each parameter is weighted according to its sensitivity to the performance of the adhesive oil, and corrections are made based on the fluctuation range of each parameter to construct a predicted environmental data set; including: S31 assigns weights to each parameter in the environmental information based on its sensitivity to the curing performance of the adhesive. Different environmental parameters have varying degrees of influence on the curing performance of the adhesive. By analyzing historical data or experimental results, the sensitivity of each parameter to the curing performance of the adhesive is quantified and weighted. This is then used in subsequent weighted average calculations and fluctuation corrections to ensure that the more important parameters have a greater impact on the predicted results. Temperature affects the reaction rate between epoxy resin and curing agent, as well as the application window; humidity affects interfacial moisture accumulation and waterproofing; and wind speed affects the uniformity of adhesive coating and the surface curing rate.

[0027] The weight distribution can be combined with the regression analysis results of historical data, that is, the bonding strength of the bonding oil is used as the target variable and the environmental information is used as the input variable. The importance of each parameter is determined through regression analysis, and the sum of the weights is 1, ensuring that subsequent calculations are simple and the results are reliable.

[0028] S32 obtains environmental information of the working hours on the construction day through the meteorological API, including time-sharing data of temperature, humidity and wind speed; specifically queries the local meteorological station or meteorological service platform to obtain forecast data for the construction period of the day. If a specific construction time window is determined, for example, from 8:00 am to 6:00 pm, the time series data of each parameter within these 10 hours is obtained. If the construction is divided into multiple stages, the environmental information of each stage is recorded separately. In the present invention, real-time acquisition of time-sharing environmental data can reflect the specific conditions of the construction day, improve the accuracy of the adjustment of the bonding oil formula, and use time-sharing data to capture environmental fluctuations during the construction period, avoiding the deviation caused by using only a single average value.

[0029] S33 calculates the fluctuation amplitude of each parameter during the working hours and corrects the fluctuation amplitude based on the weight. Environmental parameters will fluctuate during the construction period, and the potential impact of these fluctuations on the performance of the adhesive oil needs to be considered. The present invention corrects the fluctuations through weights to reflect the actual contribution of the fluctuations to the final environmental data set.

[0030] S34 combines the weighted average value and the fluctuation correction value to form an environmental data set.

[0031] Preferably, in step S33, the fluctuation amplitude is the difference between the maximum and minimum values of each parameter during the operating time. For example, if the maximum temperature is 22°C and the minimum is 18°C, the fluctuation amplitude is 4°C. If the maximum humidity is 70% and the minimum is 60%, the fluctuation amplitude is 10%. Based on the weight assigned in S31, the fluctuation amplitude is corrected: correction value = fluctuation amplitude × weight.

[0032] Preferably, in step S34, a nonlinear distribution correction method is adopted to proportionally scale the fluctuation correction value to match the actual fluctuation range, and the correction value size is dynamically adjusted by the scaling coefficient. The scheme can be flexibly adapted according to different fluctuation amplitudes, and will not cause distortion of the results due to extreme correction values, so that the correction value always remains in a reasonable range.

[0033] A smoothing factor is introduced, and a scaling factor is calculated by taking the ratio of the fluctuation amplitude to the weighted average value and the smoothing factor. The correction value is adjusted by the scaling factor, and the adjusted correction value is calculated. The weighted average value is then corrected by the adjusted correction value to obtain the fluctuation correction value.

[0034] The specific formula is as follows: Fluctuation correction value = weighted average + adjusted correction value; Adjusted correction value = correction value * scaling factor; Scaling factor = fluctuation range / (weighted average + smoothing factor); If the fluctuation is small (e.g., a fluctuation of 1.0°C), the scaling factor will be low, significantly reducing the correction value to avoid overcorrection. If the fluctuation is large, the scaling factor will be relatively high, and the correction value will be appropriately amplified to reflect the more significant fluctuation. The corrected parameter value should not exceed the actual range of the day (i.e., between the maximum and minimum values). If it does, a constraint can be added to the calculation of the corrected parameter value: Corrected parameter value = min(maximum value, max(minimum value, corrected parameter value)).

[0035] The second object of the present invention is to provide a method for preparing a second-stage epoxy adhesive for road and bridge paving. The above technical objectives of the present invention are achieved through the following technical solutions: A method for preparing a second-stage epoxy adhesive for road and bridge pavement, comprising: A1 weighs each component according to the mass ratio; A2: Epoxy resin, toughening agent, waterproofing agent, and diluent are stirred and reacted at 40-60°C for 1-2 hours to obtain main agent A. During mixing, epoxy resin is added first, followed by the toughening agent, waterproofing agent, and diluent. Each component is ensured to be evenly dispersed before adding another component. During the stirring process, the stirring speed is controlled at 100-300 rpm to avoid excessive bubble generation and ensure the uniformity and strength of the resulting adhesive layer.

[0036] A3 Stir the room temperature curing agent, latent curing agent and accelerator at 30-50°C for 1-1.5 hours to obtain curing agent B; avoid excessively high temperature which may cause the latent curing agent to react prematurely. A4: At room temperature, stir and mix the base agent A and curing agent B to obtain a second-stage epoxy adhesive. Store the prepared adhesive in a sealed container, avoiding prolonged contact with air to prevent moisture absorption or premature reaction. Maintain the storage temperature between 15°C and 25°C. Use the prepared adhesive within 2-5 hours to avoid material waste due to curing.

[0037] The third object of the present invention is to provide an application method of a second-stage epoxy adhesive for road and bridge pavement. The above technical objectives of the present invention are achieved through the following technical solutions: A method for applying a second-stage epoxy adhesive for road and bridge pavement includes the following steps: V1 Clean and pre-treat the base to be laid; the steel bridge deck needs to be sandblasted for rust removal or treated with an anti-rust coating; the concrete bridge deck is polished and cleaned to ensure that the surface is dry and pollution-free.

[0038] V2 is coated with a second-stage epoxy adhesive on the pre-treated substrate to be laid and the coating thickness is controlled. It is cured in one stage at room temperature to form a preliminarily cured thermoplastic state. The coating method includes spraying, rolling or scraping. The coating thickness is 0.5~1.5mm, which is adjusted according to different laying substrates. The first stage curing time is 2~4h. The upper paving material, specifically asphalt concrete, is paved on the surface of the second-stage epoxy adhesive oil after the first-stage curing of V3. Under high temperature conditions, the initial cured state begins to melt; then it is cured to a thermosetting state in the second stage; among them, the construction temperature of the asphalt concrete is consistent with the activation temperature of the latent curing agent, ensuring that the performance of the material can be fully exerted under actual working conditions.

[0039] After V4 curing is completed, the bonding oil and asphalt concrete form a strong interface bond.

[0040] Beneficial effects: By incorporating dynamic weighting and a fluctuation correction mechanism for environmental information (temperature, humidity, and wind speed), this invention allows the adhesive oil formulation to adjust component ratios based on the actual construction environment, ensuring excellent bonding, waterproofing, and durability under varying temperature, humidity, and climate conditions. Adjusting the curing agent ratio and formulation design allows for a smooth transition between the first stage (ambient temperature curing) and the second stage (high-temperature curing). This reduces damage to the adhesive layer by construction machinery while allowing for rapid completion of secondary curing under high-temperature paving conditions, ensuring a strong bond between the adhesive layer and the paving layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0042] Figure 1 Shown is a flow chart of the steps for preparing a second-stage epoxy adhesive for road and bridge paving. DETAILED DESCRIPTION

[0043] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, a second-stage epoxy adhesive oil for road and bridge pavement provided by the present invention, its specific implementation method, characteristics and effects are described in detail as follows.

[0044] Example 1: A second-stage epoxy adhesive for road and bridge paving, comprising a main agent A and a curing agent B. The main agent A comprises an epoxy resin, a toughening agent, a waterproofing agent, and a diluent, and the curing agent B comprises a room-temperature curing agent, a latent curing agent, and an accelerator. The ratio of the components in the main agent A and the curing agent B is adjusted based on actual paving information. Preferably, the epoxy resin in main agent A is one or more of bisphenol A epoxy resins E51, E44, E39, E20, and E12. Preferably, the epoxy resin has a molecular weight of 700-1200 g / mol and a viscosity of 0.01-0.05 Pa·s (25°C). It provides bonding strength and hardness, ensuring the adhesive oil forms a strong structure after curing. Its epoxy groups provide reactivity, allowing it to cross-link with the curing agent. The main agent A dosage accounts for 60%-80% of the total mass of main agent A. The network structure formed by the cured bisphenol A epoxy resin exhibits excellent mechanical properties, including high tensile strength, compressive strength, and shear resistance. This provides high-strength support, withstands the intense pressure of heavy traffic in road and bridge pavements, extends the service life of road and bridge pavement materials, and reduces damage caused by material fatigue or delamination.

[0045] The toughening agent is one or more of an organosilicon toughening agent, a polyether toughening agent or a liquid rubber toughening agent; Silicone toughening agents are flexible molecules containing a silicon-oxygen chain structure. The flexibility of the silicon-oxygen chain (-Si-O-Si-) enables it to improve toughness in the cured epoxy system, providing water resistance and high and low temperature resistance. Polyether toughening agents use polyethylene oxide (EO) or polypropylene oxide (PO) as the main chain segments, have a low glass transition temperature (Tg) and excellent flexibility, and enhance low-temperature toughness and fluidity. Liquid rubber toughening agents (such as CTBN and ATBN) are a type of low-molecular-weight rubber containing active end groups. They usually cross-link with epoxy resin through chemical reactions to form a block or dispersed phase structure. The rubber phase is dispersed in the cured epoxy matrix to form "micro-area toughening", which can significantly improve impact resistance and fatigue resistance.

[0046] Depending on the specific construction environment and requirements, the combination of toughening agents can achieve targeted optimization: in cold regions, polyether toughening agents are preferred, supplemented by liquid rubber; in high-humidity environments, silicone toughening agents are primarily used to enhance water resistance; in heavy traffic areas, liquid rubber toughening agents are primarily used, supplemented by polyether toughening agents to improve fatigue resistance. The preferred range of toughening agent dosage is 5% to 25% of the total weight of the main agent A.

[0047] The waterproofing agent is one or more of the following: silane coupling agents A-151, A-172, KH-540, KH-560, KH-570, KH-602, and KH-791. The bifunctional structure of the silane coupling agent, where one end reacts with the epoxy resin and the other chemically bonds to the substrate surface, enhances the bond strength between the adhesive and the substrate. The silane coupling agent improves the wettability of the substrate surface, reduces the contact angle, and improves the adhesion of the epoxy adhesive. The interfacial layer it forms resists moisture penetration, enhancing waterproofing and interfacial stability. The dosage is 2%-5% of the total weight of the main agent A.

[0048] The diluent is one or more of butyl glycidyl ether, phenyl glycidyl ether, alkyl glycidyl ether, and carbonate diluents. These diluents can adjust the viscosity and workability of the adhesive oil while ensuring compatibility with the epoxy system and participation or volatilization during the curing process. The usage level should be 5%-10% of the total mass of the main agent A. The active epoxy groups contained in butyl glycidyl ether, phenyl glycidyl ether, and alkyl glycidyl ether can participate in the curing reaction, enhancing the strength and toughness of the system. Carbonate diluents such as propylene glycol carbonate (PC) and ethylene glycol carbonate (EGC) have lower viscosity than glycidyl ethers, significantly improving workability.

[0049] Preferably, in curing agent B, the room temperature curing agent includes one or more of polyamide curing agent, polyetheramine curing agent or fatty amine curing agent, the latent curing agent includes one or more of imidazole curing agent or dicyandiamide curing agent; the accelerator is imidazole or tertiary amine. Specifically, the room temperature curing agent provides rapid initial bonding, and the latent curing agent provides final strength at high temperature. Among them, the ratio of room temperature curing agent and latent curing agent is controlled in the range of 3:1~5:1 to balance the rapid curing and high temperature curing effects. Imidazole curing agent acts as a high temperature fast starter, and dicyandiamide releases active amines at high temperature to react with epoxy resin to form a high-strength cross-linked network. Accelerators can accelerate the reaction of room temperature curing agent or latent curing agent, shorten the curing time or adjust the reaction rate, especially under low temperature or tight construction time conditions. The dosage is usually 1%~5% of curing agent B. Preferably, the accelerator is one or more of 2-methylimidazole, 2-ethylimidazole, triethylamine, and triisopropylamine.

[0050] Preferably, the mass ratio of the main agent A to the curing agent B is 2 to 4:1. Specifically, the ratio is adjusted according to the environment. In high-temperature construction environments, the diluent is reduced and the proportion of the latent curing agent is increased. In low-temperature environments, the ratio of the diluent to the room-temperature curing agent is increased to accelerate the curing speed. In high-humidity environments, the proportion of the waterproofing agent is increased while the amount of the latent curing agent is reduced to avoid performance degradation caused by excessive curing time. By dynamically adjusting the formula, the present invention can generate the optimal adhesive oil formula based on the actual construction conditions of the day, thereby improving construction quality and efficiency.

[0051] In the present invention, the curing of the second-stage epoxy adhesive oil is mainly divided into two stages: the first stage is room temperature curing: at this time, the epoxy resin in the main agent A and the room temperature curing agent in the curing agent B undergo a ring-opening polymerization reaction to form a preliminary cross-linked network, ensuring that the adhesive oil has adhesion and preliminary strength, and at the same time has a certain thermoplasticity, which can adapt to mechanical loads during construction; the second stage is high-temperature curing: specifically under high-temperature paving of asphalt concrete, the epoxy resin in the main agent A and the latent curing agent in the curing agent B react under high-temperature activation to further form a denser cross-linked network, significantly improving the mechanical strength, durability and waterproof performance of the adhesive oil, and at the same time transforming it into an irreversible thermosetting structure.

[0052] The adjustment method of the ratio includes the following steps: S1 establishes a linked data model of historical paving information, historical environmental information, and historical bonding oil formula information. Paving information includes paving base information, paving upper layer information, and construction information; environmental information includes temperature, humidity, and wind speed. Preferably, in step S1, the purpose is to build a correlation data model that can predict the bonding oil formula by analyzing historical paving data, environmental data and bonding oil formula performance, so as to provide a dynamic adjustment basis for actual construction. S11 collects historical paving information, historical environmental information, and historical adhesive oil formula information data, and pre-processes the collected historical data; Specifically, in order to obtain high-quality data, we can first determine the source of historical data, including sensor records, construction records, laboratory records, etc. After collecting historical data, we can perform data cleaning, check whether the data has missing values or outliers, and convert categorical variables into numerical variables. For data that cannot be directly expressed numerically, each information item is converted into a numerical feature. For example, the substrate type can be encoded as: steel bridge deck = 1, concrete bridge deck = 2, so that the data is at the same order of magnitude, avoiding the impact of data features on model training due to different orders of magnitude.

[0053] S12 converts the pre-processed historical data into feature vectors and constructs a feature matrix based on the feature vectors; S13 calculates a correlation matrix based on the feature matrix, optimizes the feature matrix using the correlation matrix, and standardizes the optimized feature matrix to form a historical data set; On the basis of the above embodiment, each historical data record is converted into a row of feature vectors, and all features are combined into a matrix, where each row corresponds to a sample and each column corresponds to a feature; after the data is converted into a matrix, the correlation matrix can be calculated using matrix operations such as NumPy to analyze the redundancy between data features, the contribution of features to the target, etc., to facilitate the subsequent optimization of the feature matrix. The correlation matrix can help select model input variables, including deleting highly redundant features; for features with nonlinear relationships, the introduction of polynomial features or other transformations can be considered. In order to obtain high-quality data, it is also necessary to standardize or normalize the optimized feature matrix, convert the features into zero-mean, unit variance distributions, and scale them to a uniform range to avoid the dominance of model optimization due to excessively large values in the subsequent model training process.

[0054] S14 selects a suitable neural network model to build a related data model, and uses historical data sets to train and optimize the related data model.

[0055] Specifically, the model selection process involves selecting an appropriate neural network model based on the data size and task characteristics, designing the input, hidden, and output layers for the selected model, and configuring the activation and loss functions. For model training and optimization, the historical dataset can be split into a training set and a test set. The model is trained using the training set, and the accuracy of the model is verified using the test set, ultimately resulting in a correlation data model that meets the accuracy requirements.

[0056] During actual paving, S2 obtains paving base information, paving upper layer information and construction information according to the construction plan, and summarizes them to form an actual paving data set; Preferably, in step S2, the purpose is to obtain real-time data from actual construction, including paving base, upper layer materials and construction parameters, to form a comprehensive data set to provide accurate input for subsequent binder oil formulation recommendations, wherein: Pavement base information includes base type and corresponding surface condition; base type includes steel bridge deck or concrete bridge deck, and surface condition includes roughness, moisture content and porosity; pavement base is one of the key factors in determining the selection of bonding oil formula. The base material type, condition and treatment method directly affect the bonding strength, toughness and waterproof performance of the bonding oil.

[0057] Information about the upper pavement layer includes asphalt concrete type, paving equipment, paving thickness, and paving temperature. The material and construction process of the upper pavement layer determine the thickness, curing speed, and bonding performance of the binder. Asphalt concrete types include densely graded asphalt (AC), stone aggregate asphalt (SMA), and open-graded drained asphalt (OGFC). Different asphalt mixtures have different paving temperature requirements, and the thickness of the upper pavement layer directly affects the choice and dosage of the binder.

[0058] Application information includes coating method and coating thickness.

[0059] The specific steps include: Based on the collection of paving base, upper layer and construction information, a complete set of actual paving data is formed; data collection can be carried out using tools such as infrared thermometers, laser level meters, sensors and GPS; at the construction site, a construction data collection system is used to directly upload data to the cloud database; Store the above data in a tabular or structured form to facilitate subsequent model input; Check whether the data is complete, for example, whether the base moisture content, upper layer thickness, etc. are missing. If some data is difficult to obtain in real time, empirical values or historical data can be introduced to supplement it; Then check whether there are any abnormal values (such as substrate temperature below 0°C, paving temperature below the required paving range), and ensure that the units and ranges of each parameter are consistent (such as temperature is unified in °C, speed is unified in m / min); Finally, it is organized into a standardized data structure for use in subsequent steps.

[0060] S3 obtains environmental information during the working hours of the construction day, assigns weights to each parameter based on its sensitivity to the performance of the adhesive oil, and makes corrections based on the fluctuation range of each parameter to construct a predicted environmental data set; Preferably, in step S3, environmental information of the working hours on the construction day is obtained, each parameter is weighted according to its sensitivity to the performance of the adhesive oil, and corrections are made based on the fluctuation range of each parameter to construct a predicted environmental data set; including: S31 assigns weights to each parameter in the environmental information based on its sensitivity to the curing performance of the adhesive. Different environmental parameters have varying degrees of influence on the curing performance of the adhesive. By analyzing historical data or experimental results, the sensitivity of each parameter to the curing performance of the adhesive is quantified and weighted. This is then used in subsequent weighted average calculations and fluctuation corrections to ensure that the more important parameters have a greater impact on the predicted results. Temperature affects the reaction rate between epoxy resin and curing agent, as well as the application window; humidity affects interfacial moisture accumulation and waterproofing; and wind speed affects the uniformity of adhesive coating and the surface curing rate.

[0061] The weight distribution can be combined with the regression analysis results of historical data, that is, the bonding strength of the bonding oil is used as the target variable and the environmental information is used as the input variable. The importance of each parameter is determined through regression analysis, and the sum of the weights is 1, ensuring that subsequent calculations are simple and the results are reliable.

[0062] S32 obtains environmental information of the working hours on the construction day through the meteorological API, including time-sharing data of temperature, humidity and wind speed; specifically queries the local meteorological station or meteorological service platform to obtain forecast data for the construction period of the day. If a specific construction time window is determined, for example, from 8:00 am to 6:00 pm, the time series data of each parameter within these 10 hours is obtained. If the construction is divided into multiple stages, the environmental information of each stage is recorded separately. In the present invention, real-time acquisition of time-sharing environmental data can reflect the specific conditions of the construction day, improve the accuracy of the adjustment of the bonding oil formula, and use time-sharing data to capture environmental fluctuations during the construction period, avoiding the deviation caused by using only a single average value.

[0063] S33 calculates the fluctuation amplitude of each parameter during the working hours and corrects the fluctuation amplitude based on the weight. Environmental parameters will fluctuate during the construction period, and the potential impact of these fluctuations on the performance of the adhesive oil needs to be considered. The present invention corrects the fluctuations through weights to reflect the actual contribution of the fluctuations to the final environmental data set.

[0064] S34 combines the weighted average value and the fluctuation correction value to form an environmental data set.

[0065] Preferably, in step S33, the fluctuation amplitude is the difference between the maximum and minimum values of each parameter during the operating time. For example, if the maximum temperature is 22°C and the minimum is 18°C, the fluctuation amplitude is 4°C. If the maximum humidity is 70% and the minimum is 60%, the fluctuation amplitude is 10%. Based on the weight assigned in S31, the fluctuation amplitude is corrected: correction value = fluctuation amplitude × weight.

[0066] Preferably, in step S34, a nonlinear distribution correction method is adopted to proportionally scale the fluctuation correction value to match the actual fluctuation range, and the correction value size is dynamically adjusted by the scaling coefficient. The scheme can be flexibly adapted according to different fluctuation amplitudes, and will not cause distortion of the results due to extreme correction values, so that the correction value always remains in a reasonable range.

[0067] A smoothing factor is introduced, and a scaling factor is calculated by taking the ratio of the fluctuation amplitude to the weighted average value and the smoothing factor. The correction value is adjusted by the scaling factor, and the adjusted correction value is calculated. The weighted average value is then corrected by the adjusted correction value to obtain the fluctuation correction value.

[0068] The specific formula is as follows: Fluctuation correction value = weighted average + adjusted correction value; Adjusted correction value = correction value * scaling factor; Scaling factor = fluctuation range / (weighted average + smoothing factor); If the fluctuation is small (e.g., a fluctuation of 1.0°C), the scaling factor will be low, significantly reducing the correction value to avoid overcorrection. If the fluctuation is large, the scaling factor will be relatively high, and the correction value will be appropriately amplified to reflect the more significant fluctuation. The corrected parameter value should not exceed the actual range of the day (i.e., between the maximum and minimum values). If it does, a constraint can be added to the calculation of the corrected parameter value: Corrected parameter value = min(maximum value, max(minimum value, corrected parameter value)).

[0069] S4 inputs the actual paving data set and the predicted environment data set into the associated data model and outputs the recommended bonding oil formula on the construction day.

[0070] By incorporating dynamic weighting and a fluctuation correction mechanism for environmental information (temperature, humidity, and wind speed), this invention allows the adhesive oil formulation to adjust component ratios based on the actual construction environment, ensuring excellent bonding, waterproofing, and durability under varying temperature, humidity, and climate conditions. Adjusting the curing agent ratio and formulation design allows for a smooth transition between the first stage (ambient temperature curing) and the second stage (high-temperature curing). This reduces damage to the adhesive layer by construction machinery while allowing for rapid completion of secondary curing under high-temperature paving conditions, ensuring a strong bond between the adhesive layer and the paving layer.

[0071] Example 2: A method for preparing a second-stage epoxy adhesive for road and bridge pavement, comprising: A1 weighs each component according to the mass ratio; A2: Epoxy resin, toughening agent, waterproofing agent, and diluent are stirred and reacted at 40°C for 1 hour to obtain main agent A. During mixing, epoxy resin is added first, followed by the toughening agent, waterproofing agent, and diluent. Each component is ensured to be evenly dispersed before adding another component. The stirring speed is controlled at 200 rpm during the stirring process to avoid excessive bubble generation and ensure the uniformity and strength of the resulting adhesive layer.

[0072] A3 Stir the room temperature curing agent and the latent curing agent at 40°C for 1 hour to obtain curing agent B; avoid excessively high temperature which may cause the latent curing agent to react prematurely. A4: At room temperature, stir and mix the base agent A and curing agent B to obtain a second-stage epoxy adhesive. Store the prepared adhesive in a sealed container, avoiding prolonged contact with air to prevent moisture absorption or premature reaction. Maintain the storage temperature at 25°C. Use the prepared adhesive within 2-5 hours to avoid material waste due to curing.

[0073] A method for applying a second-stage epoxy adhesive for road and bridge pavement includes the following steps: V1 cleans and pre-treats the base to be laid; the base is a steel bridge deck, which has been sandblasted and derusted, with a surface roughness of Ra = 50 µm, a surface moisture content of 0.5%, and a base temperature of 15°C. V2 is to apply second-stage epoxy adhesive oil on the pre-treated base to be laid and control the coating thickness. It is cured in one stage at room temperature to form a preliminary cured thermoplastic state. The bonding layer requires mechanical spraying of 0.8mm, and the construction time is from 8:00 am to 2:00 pm.

[0074] V3 is paved on the surface of the second-stage epoxy adhesive after the first-stage curing. Under high temperature conditions, the initial cured state begins to melt; then it is cured to a thermosetting state in the second stage; After V4 curing is completed, the bonding oil and asphalt concrete form a strong interface bond.

[0075] Those skilled in the art will appreciate that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A second-stage epoxy adhesive for road and bridge paving, characterized in that: It includes a main agent A and a curing agent B. The main agent A includes an epoxy resin, a toughening agent, a waterproofing agent and a diluent. The curing agent B includes a room temperature curing agent, a latent curing agent and an accelerator. The ratio of the components in the main agent A and the curing agent B is adjusted according to the actual paving information. The method for adjusting the ratio includes the following steps: S1 establishes a correlation data model of historical paving information, historical environmental information, and historical bonding oil formula information, wherein the paving information includes paving base information, paving upper layer information, and construction information; and the environmental information includes temperature, humidity, and wind speed; During actual paving, S2 obtains paving base information, paving upper layer information and construction information according to the construction plan, and summarizes them to form an actual paving data set; S3 obtains environmental information during the working hours of the construction day, assigns weights to each parameter based on its sensitivity to the performance of the adhesive oil, and makes corrections based on the fluctuation range of each parameter to construct a predicted environmental data set; S4 inputs the actual paving data set and the predicted environment data set into the associated data model, and outputs the bonding oil formula recommended on the construction day.

2. The second-stage epoxy adhesive for road and bridge pavement according to claim 1, characterized in that: In the main agent A, the epoxy resin is one or more of bisphenol A epoxy resin E51, E44, E39, E20, and E12; The toughening agent is one or more of an organosilicon toughening agent, a polyether toughening agent or a liquid rubber toughening agent; The waterproofing agent is one or more of silane coupling agents A-151, A-172, KH-540, KH-560, KH-570, KH-602, and KH-791; The diluent is one or more of butyl glycidyl ether, phenyl glycidyl ether, alkyl glycidyl ether and carbonate diluent.

3. The second-stage epoxy adhesive for road and bridge pavement according to claim 1, characterized in that: In the curing agent B, the room temperature curing agent includes one or more of a polyamide curing agent, a polyetheramine curing agent or a fatty amine curing agent, the latent curing agent includes one or more of an imidazole curing agent or a dicyandiamide curing agent; and the accelerator is imidazole or a tertiary amine.

4. The second-stage epoxy adhesive for road and bridge pavement according to claim 1, characterized in that: Step S1 includes: S11 collects historical paving information, historical environmental information, and historical adhesive oil formula information data, and pre-processes the collected historical data; S12 converts the pre-processed historical data into feature vectors, and constructs a feature matrix based on the feature vectors; S13: calculating a correlation matrix based on the feature matrix, optimizing the feature matrix using the correlation matrix, and standardizing the optimized feature matrix to form a historical data set; S14 selects a suitable neural network model to construct a correlation data model, and uses the historical data set to train and optimize the correlation data model.

5. The second-stage epoxy adhesive for road and bridge pavement according to claim 1, characterized in that: In step S2, The pavement base information includes a base type and a surface condition corresponding to the base type; the base type includes a steel bridge deck or a concrete bridge deck, and the surface condition includes roughness, moisture content, and porosity; The paving upper layer information includes asphalt concrete type, paving equipment, paving thickness and paving temperature; The construction information includes coating method and coating thickness.

6. The second-stage epoxy adhesive for road and bridge pavement according to claim 1, characterized in that: Step S3 includes: S31 assigns weights to each parameter in the environmental information according to its sensitivity to the curing performance of the adhesive oil; S32 uses the weather API to obtain environmental information during working hours on construction days, including time-sharing data on temperature, humidity, and wind speed; S33 calculates the fluctuation range of each parameter during the working time, and corrects the fluctuation range based on the weight; S34 combines the weighted average value and the fluctuation correction value to form an environmental data set.

7. The second-stage epoxy adhesive for road and bridge pavement according to claim 6, characterized in that: In step S33 , the fluctuation amplitude is the difference between the maximum value and the minimum value of each parameter during the working time.

8. The second-stage epoxy adhesive for road and bridge pavement according to claim 6, characterized in that: In step S34, a smoothing factor is introduced, and a scaling factor is calculated using the ratio of the fluctuation amplitude to the weighted average value and the smoothing factor. The correction value is adjusted using the scaling factor, and the adjusted correction value is calculated. The weighted average value is then corrected using the adjusted correction value to obtain a fluctuation correction value.

9. The method for preparing a second-stage epoxy adhesive for road and bridge pavement according to any one of claims 1 to 8, wherein: include: A1 weighs each component according to the mass ratio; A2: Stir and react epoxy resin, toughening agent, waterproofing agent and diluent at 40-60°C for 1-2 hours to obtain main agent A; A3: Stir the room temperature curing agent, latent curing agent and accelerator at 30-50°C for 1-1.5 hours to obtain curing agent B; A4 At room temperature, stir and mix the main agent A and curing agent B to obtain a second-stage epoxy adhesive oil.

10. A method for applying the second-stage epoxy adhesive oil for road and bridge pavement prepared by the method according to claim 9, characterized in that: The steps are as follows: V1 Clean and pre-treat the substrate to be laid; V2: Apply second-stage epoxy adhesive oil on the pre-treated substrate to be laid and control the coating thickness. Perform a one-stage curing at room temperature to form a preliminarily cured thermoplastic state. The upper layer of paving material is paved on the surface of the second-stage epoxy adhesive oil after the first-stage curing of V3. Under high temperature conditions, the initial cured state begins to melt; then it is cured to a thermosetting state in the second stage; After V4 curing is completed, the adhesive oil and the upper paving material form a strong interface bond.

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