Construction method of self-sensing asphalt concrete pavement structure

Abstract

The invention relates to a construction method of a self-sensing asphalt concrete pavement structure, which comprises the following steps: mixing natural mineral aggregate with wood biomass, and carrying out high-temperature treatment under the protection of nitrogen to form a graphitized carbon layer to obtain low-resistance aggregate with the resistivity of less than or equal to 1 * 10 <-3 > omega.m; the low-resistance-value aggregate is used for replacing the conventional aggregate according to the mass ratio of 70-90%, and a conductive asphalt mixture is prepared; a conductive asphalt mixture is used for paving a pavement, and an electrode slice is arranged to be connected with monitoring equipment. Under the action of the vehicle load, the change of the contact state among aggregates causes real-time change of the road surface resistance value. Compared with the prior art, the method has the advantages that sensitivity response of 0.5-5 omega / KN is generated by utilizing the fact that the contact resistance of the graphitized carbon layer fluctuates within the range of 0.1-100 omega, when the abnormal drifting of the resistance is larger than 15% or waveform distortion occurs, the fatigue crack propagation critical point can be judged, and therefore the asphalt concrete road structure is endowed with the intelligent self-sensing function.

Description

Technical Field

[0001] The invention relates to the field of road engineering, and in particular to a method for constructing a self-sensing asphalt concrete pavement structure. Background Art

[0002] With the rapid development of road traffic infrastructure, intelligent and information-based road structures have become an important development direction of modern transportation systems. As a new type of functional pavement material, self-sensing asphalt concrete pavement can monitor pavement status, traffic flow and structural damage in real time, provide data support for road management and maintenance, and has broad application prospects.

[0003] At present, the research on self-sensing asphalt concrete pavement mainly focuses on building a conductive network by adding conductive materials to enable the pavement to have the ability to respond to changes in electrical properties. A common technical route is to add conductive fillers, such as carbon black, carbon fiber, graphite, metal particles, etc., to the asphalt mixture to form a conductive path. For example, CN113185190A discloses a self-sensing intelligent conductive asphalt pavement material, which forms an intelligent aggregate unit by doping the asphalt mixture with conductive materials and coating the surface of the coarse aggregate with a conductive cement-based coating, thereby realizing intelligent monitoring of the dynamic response of the pavement under vehicle load. CN117107576A proposes an open parking lot intelligent management system based on self-sensing asphalt concrete pavement. By adding stainless steel microwires or using it in combination with nanofillers, the asphalt concrete is given conductivity and sensing properties, thereby realizing dynamic monitoring of vehicle parameters.

[0004] In terms of the selection of conductive materials, graphene and its derivatives have attracted wide attention due to their excellent conductive properties. CN114892469A introduces a heating road based on graphene concrete, which uses the conductive properties of graphene concrete to achieve electric heat conversion and is used to melt ice and snow on the road surface. CN115196909A discloses a self-inductive conductive asphalt concrete and its preparation method, which uses conductive materials such as chopped carbon fiber, graphite, carbon nanotubes, graphene, etc., and improves dispersibility through surfactant modification.

[0005] In terms of the application of self-sensing pavement, CN110184886A proposed a white-on-black pavement health detection system and method, which monitors the internal stress changes and fracture conditions of the pavement structure by adding conductive materials such as graphite powder and carbon fiber to the stress absorption layer and measuring the changes in the resistance value between electrodes.

[0006] However, there are still some urgent problems to be solved in the self-sensing asphalt concrete pavement in the existing technology: first, the traditional filling conductive phase has poor distribution uniformity in the asphalt mixture, and it is easy to agglomerate or separate during the mixing process, resulting in local uneven conductivity and affecting the sensing accuracy; second, the interfacial bonding between the conductive filler and the aggregate and asphalt is weak. After being affected by traffic loads, environmental erosion and temperature changes for a long time, the conductive network is easily destroyed, resulting in a decline in sensing performance; third, a high amount of conductive filler may reduce the mechanical properties of the mixture, resulting in a decrease in material strength and affecting the durability of the road.

[0007] In addition, in the prior art, conductive fillers are mostly added materials, which increases the engineering cost and is difficult to ensure uniform dispersion during the mixing process of asphalt mixture, affecting the stability and continuity of the conductive network. At the same time, the compatibility problem between the added conductive material and the asphalt matrix also limits the long-term service performance of the self-sensing pavement.

[0008] Therefore, there is an urgent need to develop a new method for constructing a self-sensing asphalt concrete pavement structure that can form a stable and uniform conductive network to ensure the reliability and durability of the sensing performance without affecting the conventional mechanical properties and durability of the pavement. Summary of the invention

[0009] The purpose of the present invention is to provide a method for constructing a self-sensing asphalt concrete pavement structure in order to overcome the defects of the above-mentioned prior art, solve the problems of uneven distribution of conductive phase, weak interface bonding force and decreased mechanical properties in traditional self-sensing asphalt concrete pavement, realize the construction of a high-stability conductive network and enhance long-term self-sensing capabilities.

[0010] The purpose of the present invention can be achieved by the following technical solutions:

[0011] The present invention provides a method for constructing a self-sensing asphalt concrete pavement structure, comprising the following steps:

[0012] S1: natural mineral aggregates are mixed with wood biomass, and after mechanical stirring, the temperature is raised to 800-1100°C under nitrogen protection, and the temperature is kept for 30-120 minutes to form a graphitized carbon layer. After annealing and screening, a low-resistance aggregate with a surface coated with a continuous graphitized carbon layer and a resistivity of ≤1×10-3Ω·m is obtained;

[0013] S2: The low-resistance aggregate obtained in S1 is used to replace the conventional aggregate at a mass ratio of 70-90%, combined with asphalt binder and filler, to prepare a conductive asphalt mixture according to the continuous grading requirements;

[0014] S3: Use the conductive asphalt mixture obtained in S2 for road paving. Under the action of vehicle load, the resistance value of the entire road surface changes in real time due to the change in the contact state between aggregates and the microstructure adjustment of the conductive network. By monitoring the resistance change law, road structure strain monitoring, traffic flow monitoring, and fatigue damage warning are realized, thereby giving the asphalt concrete road structure intelligent self-sensing function.

[0015] Furthermore, S3 further includes the setting of an electrode sheet, wherein the electrode sheet is used to be connected to a device for monitoring a law of resistance change, and the setting process of the electrode sheet includes:

[0016] Two electrodes were placed on both sides of the uncured asphalt concrete specimen.

[0017] or,

[0018] After 0.2-0.8 cm of graphite powder was evenly coated on both sides of the cured asphalt concrete specimen, two electrode sheets were placed on the graphite powder.

[0019] Furthermore, in S3, the electrode layout meets the JTG E20-2011 standard to ensure a low resistance path with the modified aggregate conductive network.

[0020] Furthermore, in S3, the device for monitoring the resistance change law is an LCR bridge, and the resistance value change between electrodes is monitored by the LCR bridge at a sampling frequency of ≤100ms:

[0021] When a vehicle load of 1-100KN is applied, the contact resistance of the graphitized carbon layer fluctuates in the range of 0.1-100Ω, resulting in a sensitivity response of 0.5-5Ω / KN.

[0022] Furthermore, in S3, the process of realizing road structure strain monitoring, traffic flow monitoring, and fatigue damage early warning includes:

[0023] Strain monitoring: Invert the local strain distribution of the pavement through the resistance-stress linear relationship;

[0024] Traffic sensing: using the resistance fluctuation frequency to identify the number of vehicle passes and axle weight;

[0025] Damage warning: When the abnormal resistance drift is greater than 15% or the waveform is distorted, it is determined to be the critical point of fatigue crack extension.

[0026] Furthermore, in S1, the woody biomass is selected from at least one of bamboo powder, sawdust, bagasse, cotton fiber, and coconut shell fiber, the carbon content in the woody biomass is ≥40wt%, and after being crushed to 50-300 mesh, it is wrapped on the surface of the natural mineral in a volume ratio of 1:10-1:20 through mechanical stirring.

[0027] Furthermore, in S1, the particle size of the natural mineral aggregate is 2.36-31.5 mm, and the natural mineral aggregate is basalt, granite, limestone or siliceous sandstone with a surface roughness Ra≥50 μm.

[0028] Further, in S1, the process of forming the graphitized carbon layer specifically includes: heating to 800-1100°C at a heating rate of 5-10°C / min, and keeping warm for 30-120 minutes to generate a carbonized layer containing 3-10 graphene sheets, and the ID / IG value is ≤0.25.

[0029] Furthermore, in S1, the annealing treatment adopts a gradient cooling process: the temperature is reduced from the pyrolysis temperature to a constant temperature platform of 600-800°C at a rate of 5°C / min and maintained for 30 minutes. During the natural cooling process, the oxygen content is ≤50ppm, and finally a continuous carbonized layer with a thickness of 10-200μm and a thermal conductivity of ≥120W / (m·K) is obtained.

[0030] Furthermore, in S1, the electrode is one of copper, stainless steel and graphite with an electrical conductivity greater than 105 S / m.

[0031] The core technical mechanism of the present invention is to realize the integration of sensing functions through the microstructure regulation and interface coupling effect of the graphitized carbon layer in the asphalt matrix: to give the material a highly sensitive piezoresistive property (strain-resistance linear response), combined with a low-defect graphitized structure (ID / IG≤0.25) to ensure the stability of the conductive network; through the gradient distribution design of the carbon layer in the asphalt, the mechanical deformation is converted into a resistance change signal, and the resistance fluctuation spectrum under dynamic load is used to analyze the vehicle axle weight and traffic frequency, and at the same time, the time cumulative damage model is combined to correlate the resistance drift law and material fatigue life.

[0032] The core technical mechanism of the present invention is that, through in-situ graphitization and carbonization technology, a highly crystalline graphitized carbon layer is grown on the surface of the aggregate, so that the conductive phase forms a firm bond with the aggregate, fundamentally improving the stability of the conductive network. Compared with the traditional filling method, the low-resistance aggregate of the present invention not only ensures the uniform distribution of the conductive network, but also has a more stable electrical response under vehicle load and environmental changes, and is not prone to resistance drift.

[0033] The application of the graphitized carbon layer modified low-resistance aggregate in the self-sensing of asphalt concrete pavement has the following beneficial effects:

[0034] 1) The present invention uses resistance changes to monitor vehicle loads, stress distribution, and crack expansion, achieving real-time monitoring and early warning of road health status, improving road safety and maintenance efficiency, and providing technical support for smart transportation infrastructure. When a vehicle load of 1-100KN is applied, the contact resistance of the graphitized carbon layer fluctuates in the range of 0.1-100Ω, generating a sensitivity response of 0.5-5Ω / KN. The local strain distribution of the road surface can be inverted through the resistance-stress linear relationship, and the frequency of resistance fluctuations can be used to identify the number of vehicle passes and axle weights. When the abnormal resistance drift is greater than 15% or the waveform is distorted, it can be determined as the critical point of fatigue crack expansion, achieving damage early warning.

[0035] 2) The present invention grows a high-crystallinity graphitized carbon layer in situ on the aggregate surface, so that the conductive phase is closely combined with the aggregate to construct a stable and uniform conductive network, avoiding the uneven dispersion and interface shedding problems of traditional filled conductive materials, and ensuring the long-term reliability of the self-sensing function. Compared with traditional filled conductive materials (such as carbon black, carbon fiber, metal particles, etc.), which rely on the additional addition of conductive fillers and easily lead to the problem of uneven distribution of the conductive phase, the present invention forms a stable embedded conductive network, avoiding the dispersion problem of the filling method, and has higher conductive stability, better durability and better engineering adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Schematic diagram of the mechanism of the road surface self-sensing process in the present invention;

[0037] In the figure: 1. Vehicle, 2. Road surface structure, 3. LCR bridge.

[0038] Figure 2 This is a graph showing the change in resistance value of self-sensing asphalt concrete specimens under cyclic loading. DETAILED DESCRIPTION

[0039] The present invention mainly studies the preparation method of asphalt concrete for realizing road pressure self-sensing response, and part of the aggregates in the asphalt concrete are low-resistance aggregates. The low-resistance aggregates construct a 3D conductive network in the asphalt concrete. As the road load changes, the intersection and separation relationship between the aggregates changes, and the conductive network changes accordingly. The road resistance collected by the electrodes in the self-sensing road surface will change, thereby realizing the conversion of pressure-electrical signals, that is, realizing road surface self-sensing. It mainly includes the following steps:

[0040] Biomass loading: natural mineral aggregate with a particle size of 2.36-31.5 mm and woody biomass with a particle size of 50-300 mesh are mixed at a volume ratio of 1:10-1:20, and the woody biomass is evenly coated on the surface of the natural mineral aggregate by mechanical stirring to obtain biomass-loaded aggregate;

[0041] High temperature pyrolysis carbonization: Under nitrogen protection, the biomass-loaded aggregate is heated to 800-1100°C and kept at this temperature for 30-120 minutes to generate an in-situ graphitized carbon layer;

[0042] Annealing treatment: The pyrolyzed aggregate is treated at a constant temperature of 600-800℃ for 10-60 minutes, and then the particle size is screened to obtain low-resistance aggregate. The surface of the aggregate to be modified is covered with biomass, and a graphitized carbon layer is grown in situ on the surface of the aggregate through high-temperature treatment. The modified aggregate is used to prepare asphalt concrete, and the modified asphalt concrete has self-sensing ability.

[0043] According to JTG E-20-2011 “Test Procedures for Asphalt and Asphalt Mixtures in Highway Engineering”, self-sensing asphalt concrete was made into standard test specimens.

[0044] Two metal or carbon material electrodes are placed on opposite sides of the uncured asphalt concrete specimen. Alternatively, after 0.2-0.8 cm of graphite powder is evenly coated on two opposite sides of the cured asphalt concrete specimen, two metal or carbon material electrodes are placed on the graphite powder.

[0045] Turn on the LCR bridge and connect the positive and negative electrodes to the two electrodes of the concrete specimen until the resistance reading is stable.

[0046] According to JTG E-20-2011 "Testing Procedures for Asphalt and Asphalt Mixtures in Highway Engineering", 1-100KN vehicle loads were applied to asphalt concrete specimens by simulating traffic loads;

[0047] As the load changes, the resistance value of the LCR bridge changes, and the law of changes in the asphalt concrete structure caused by the load change is extracted (when a vehicle load of 1-100KN is applied, the contact resistance of the graphitized carbon layer fluctuates in the range of 0.1-100Ω, resulting in a sensitivity response of 0.5-5Ω / KN).

[0048] In the process of realizing road structure strain monitoring, traffic flow monitoring, and fatigue damage early warning based on the change law of asphalt concrete organization, it includes:

[0049] Strain monitoring: Invert the local strain distribution of the pavement through the resistance-stress linear relationship;

[0050] Traffic sensing: using the resistance fluctuation frequency to identify the number of vehicle passes and axle weight;

[0051] Damage warning: When the abnormal resistance drift is greater than 15% or the waveform is distorted, it is determined to be the critical point of fatigue crack extension.

[0052] In a specific implementation, the woody biomass is selected from natural high-carbon content materials such as bamboo powder, wood chips, bagasse, cotton fiber, and coconut shell fiber.

[0053] In specific implementation, the aggregate is selected from basalt, granite, limestone, siliceous sandstone or other natural mineral aggregates suitable for asphalt mixture.

[0054] In specific implementation, the specific temperature range of the high-temperature pyrolysis treatment is 800-1100° C. to optimize the graphitization degree and thermal conductivity of the carbonized layer on the surface of the aggregate.

[0055] In a specific implementation, the high-temperature pyrolysis time is controlled within 30 to 120 minutes to ensure that the biomass is fully carbonized and a continuous and uniform graphene-like carbonized layer is formed.

[0056] In a specific implementation, the annealing treatment is performed at a constant temperature of 600 to 800° C. for 10 to 60 minutes to reduce structural defects in the carbonized layer and improve thermal stability.

[0057] In specific implementation, the screening process adopts a particle size screening of 2.36 to 31.5 mm to ensure that the aggregate particle size is suitable for the grading requirements of the asphalt mixture.

[0058] In the specific implementation, the unmodified aggregate is immersed in distilled water, and cleaned in an ultrasonic cleaner at a water temperature of 20-30°C for 5-10 minutes to remove surface dust and stains. After cleaning, it is dried in an oven at 80-120°C for 1-3 hours to remove excess moisture in the aggregate until the weight of the aggregate to be modified no longer changes to obtain the aggregate to be modified. The aggregate to be modified that has passed the preliminary treatment is placed in a 20-30°C forced air oven for 24 hours and stored in a dark and dry place for use.

[0059] In the specific implementation, the biomass waste is placed in a cool place to dry naturally for 24 to 48 hours, the air-dried biomass waste is sieved to remove the dust mixed therein, and further dried at 60 to 150° C. for 3 to 30 hours. After the waste biomass that has passed the preliminary treatment is cooled to room temperature, it is stored in a dark and dry place for future use.

[0060] In a specific implementation, the standby biomass waste is crushed to a fineness of 50-300 meshes, and after the broken particles are sieved, the 50-300 mesh biomass waste particles and the mixture of the aggregate to be modified are mechanically stirred at a low speed of 20-50 r / min to wrap the biomass waste particles on the surface of the aggregate to be modified.

[0061] In a specific implementation, according to the above-mentioned volume ratio of the aggregate to be modified to the biomass waste being 1:10 to 1:20, the volume of the aggregate to be modified is measured by the drainage method, and the volume of the biomass waste powder is measured by the vibration funnel method.

[0062] The pyrolysis temperature is 800-1100°C, and the heating rate of the pyrolysis process is 5°C / min-10°C / min. The heating process of the pyrolysis stage is: starting from room temperature, the temperature is increased to the pyrolysis temperature at a heating rate of 5°C / min-10°C / min.

[0063] In a specific implementation, the carbonization process is to keep the temperature at 800-1100° C. for 50-70 minutes.

[0064] In a specific implementation, the modified aggregate replaces ordinary aggregate, and self-sensing asphalt concrete is prepared according to JTG E20-2011 "Test Procedures for Asphalt and Asphalt Mixtures in Highway Engineering".

[0065] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. Component models, material names, connection structures, control methods, algorithms and other features not clearly described in this technical solution are all considered to be common technical features disclosed in the prior art.

[0066] Example 1

[0067] 1. Select basalt aggregate with a particle size greater than or equal to 2.36. Further, use an ultrasonic cleaner to clean the aggregate to be modified in a 27°C water bath environment for 20 minutes to obtain an aggregate with no sand or stains on the surface. The surface roughness Ra = 85μm (white light interferometer test). Further, dry the cleaned aggregate in a 100°C oven for 24 hours until the aggregate weight no longer changes.

[0068] 2. Sugarcane stalks are the source of life for all things. Wash the sugarcane stalks, crush them and dry them at 35℃ for 24 hours until the quality of the sugarcane debris no longer changes. Crush the sugarcane debris into 300 mesh powder for later use.

[0069] 3. Mechanically stir 1 volume of aggregate and 12 volumes of sugarcane powder for 2 minutes to disperse the aggregate in the sugarcane powder. Pour the mixture into a crucible and spread 1 volume of sugarcane on top of the mixture to ensure that no aggregate is exposed. Mechanically compact the mixture in the crucible, cover the crucible with a lid, and place it in a muffle furnace.

[0070] 4. Nitrogen is introduced into the muffle furnace for 30 minutes at a flow rate of 50 ml / min. After the muffle furnace is filled with inert gas, the modification reaction temperature is set. The starting temperature is the temperature in the muffle furnace at that moment, and the temperature is raised to 900°C at 8°C / min. The temperature is kept at 900°C for 60 minutes for full carbonization reaction. The annealing method is to cool naturally from 900°C to room temperature. After the reaction is completed, the mixture in the muffle furnace is sieved to obtain the modified aggregate.

[0071] According to the four-probe detection method, the conductivity of the carbonized material of sugarcane powder on the aggregate surface is 0.049Ω / cm, the thickness of the graphitized carbon layer is 50μm, and the thermal conductivity is 150W / (m·K). Through Raman spectroscopy testing, the ID / IG value is 0.20.

[0072] 5. According to the JTG E-20-2011 "Highway Engineering Asphalt and Asphalt Mixture Test Procedure", a cylindrical Marshall specimen with a diameter of 101 mm and a height of 63 mm was formed by the Marshall standard compaction molding method. Among them, there are two parallel control specimens W1 and W2 prepared with unmodified aggregates, and two specimens D1 and D2 prepared with modified aggregates. Among them, the asphalt used in the unmodified specimens and modified specimens is the Korean SK-70 base asphalt.

[0073] 6. Place the asphalt mixture in the UTM machine. Considering the various vehicles on the road, the maximum stress is set to 0.9 MPa. It is subjected to 10 load cycles. After each loading cycle is loaded to 0.9 MPa at 500 N / s, it is unloaded at the same rate. The interval between each stress cycle is 20 seconds.

[0074] Two stainless steel electrodes were placed on both sides of the uncured asphalt concrete specimen and connected to an LCR bridge. The LCR bridge model was Agilent E4980A, and the sampling frequency was set to 50ms to monitor the change in the resistance value between the electrodes.

[0075] During the paving process, the electrodes were laid out according to the JTG E20-2011 standard, with an electrode spacing of 20 cm. The electrodes were made of stainless steel sheets with a conductivity of 1.45×106S / m, a thickness of 1mm, a width of 5cm, and a length of 10cm.

[0076] Figure 1 The schematic diagram of the self-sensing asphalt concrete pavement generating regular electrical signals under the action of force. Among them, the vehicle 1 running on the road generates a load on the road surface structure 2, and the connection or separation relationship between the modified aggregates in the road surface structure 2 changes under the action of pressure, and the conductive network in the road surface changes, so that the resistance signal collected by the LCR bridge 3 through the electrodes in the road surface changes regularly.

[0077] Among them, the resistance of the unmodified asphalt concrete specimens W1 and W2 did not change under the load, and the resistance signal collected by the LCR bridge did not change regularly and had almost no fluctuation.

[0078] Figure 2 The resistance value of modified asphalt concrete specimens under load changes. Figure 2It can be seen that the modified asphalt concrete specimens produce obvious resistance changes under regular loads. The first load causes the specimen resistance to drop rapidly. After the load is unloaded, the resistance rises, but it does not rise to the initial resistance. Afterwards, as the load is loaded and unloaded, the specimen resistance drops and rises accordingly. After 7 loads, the resistance change trend gradually changes from a triangular wave to a rectangular wave. This is mainly because as the load cycle proceeds, the stress-strain curve of the material begins to lag and exhibit plastic deformation. This means that the material cannot fully rebound, resulting in a decrease in the resistance's recovery ability, thus forming a resistance change that is closer to a rectangular wave. In addition, during the first few loads, the contact between the conductive particles is reversible, but as the load cycle increases, the contact state between the particles gradually becomes stable, that is, under the maximum load, the change amplitude of the conductive network decreases, causing the resistance to stabilize at high loads, making the top of the waveform closer to a rectangle.

[0079] From the above conclusions, it can be seen that the modified asphalt concrete specimens prepared with sugarcane modified aggregates have self-sensing capabilities and can produce regular electrical signal changes under load.

[0080] By monitoring the resistance change pattern, the following functions are realized:

[0081] Strain monitoring: Establishing a linear relationship model between resistance and stress R = R 0 (1+kε), where R 0 is the initial resistance value, k is the sensitivity coefficient, and ε is the strain value. The local strain distribution of the pavement is inverted by this model, and the strain measurement accuracy reaches ±50με.

[0082] Traffic perception: Use the resistance fluctuation frequency to identify the number of vehicle passes and axle weight. When a vehicle passes, the resistance value shows obvious peak and trough characteristics. Through waveform feature analysis, the number of vehicle passes can be accurately identified with a recognition rate of 95%; the vehicle axle weight can be estimated through the peak value with an accuracy of ±10%.

[0083] Damage warning: Through long-term monitoring of the resistance value change trend, when the abnormal resistance drift exceeds 15% or the waveform is obviously distorted, it is determined to be the critical point of fatigue crack expansion, and early warning of road damage is given.

[0084] Example 2

[0085] The following process is different from Example 1:

[0086] In this embodiment, the biomass source is bamboo, which is crushed into 200-mesh particles, and 1 volume of aggregate is mixed with 15 volumes of bamboo powder.

[0087] The temperature was raised to 1000°C at a rate of 10°C / min, carbonized for 60 min, and then naturally cooled and annealed to room temperature.

[0088] According to the four-probe detection method, the conductivity of the carbonized bamboo powder on the aggregate surface is 0.073Ω / cm. The thickness of the graphitized carbon layer is 30μm, and the thermal conductivity is 130W / (m·K). Through Raman spectroscopy testing, the ID / IG value is 0.23.

[0089] With the application of cyclic load, regular and clear triangular waves and rectangular waves are generated.

[0090] Strain monitoring: Establishing a linear relationship model between resistance and stress R = R 0 (1+kε), where R 0 is the initial resistance value, k is the sensitivity coefficient, and ε is the strain value. The local strain distribution of the pavement is inverted by this model, and the strain measurement accuracy reaches ±50με.

[0091] Traffic perception: Use the resistance fluctuation frequency to identify the number of vehicle passes and axle weight. When a vehicle passes, the resistance value shows obvious peak and trough characteristics. Through waveform feature analysis, the number of vehicle passes can be accurately identified with a recognition rate of 95%; the vehicle axle weight can be estimated through the peak value with an accuracy of ±10%.

[0092] Damage warning: Through long-term monitoring of the resistance value change trend, when the abnormal resistance drift exceeds 15% or the waveform is obviously distorted, it is determined to be the critical point of fatigue crack expansion, and early warning of road damage is given.

[0093] Example 3

[0094] The following process is different from Example 1:

[0095] In this embodiment, the biomass source is cypress, which is crushed to 200 meshes, and the volume ratio of aggregate to cypress powder is 1:15.

[0096] The temperature was raised to 1000°C at a rate of 10°C / min, carbonized for 60 min, and then naturally cooled and annealed to room temperature.

[0097] According to the four-probe detection method, the conductivity of the carbonized bamboo powder on the aggregate surface is 0.121Ω / cm. The thickness of the graphitized carbon layer is 200μm, and the thermal conductivity is 120W / (m·K). Through Raman spectroscopy testing, the ID / IG value is 0.18

[0098] Regular triangular and rectangular waves are generated with the application of cyclic loads.

[0099] With the application of cyclic load, regular and unclear triangular waves are generated.

[0100] Strain monitoring: Establishing a linear relationship model between resistance and stress R = R 0 (1+kε), where R 0is the initial resistance value, k is the sensitivity coefficient, and ε is the strain value. The local strain distribution of the pavement is inverted by this model, and the strain measurement accuracy reaches ±50με.

[0101] Traffic perception: Use the resistance fluctuation frequency to identify the number of vehicle passes and axle weight. When a vehicle passes, the resistance value shows obvious peak and trough characteristics. Through waveform feature analysis, the number of vehicle passes can be accurately identified with a recognition rate of 95%; the vehicle axle weight can be estimated through the peak value with an accuracy of ±10%.

[0102] Damage warning: Through long-term monitoring of the resistance value change trend, when the abnormal resistance drift exceeds 15% or the waveform is obviously distorted, it is determined to be the critical point of fatigue crack expansion, and early warning of road damage is given.

[0103] The above description of the embodiments is to facilitate the understanding and use of the invention by those skilled in the art. It is obvious that those skilled in the art can easily make various modifications to these embodiments and apply the general principles described herein to other embodiments without creative work. Therefore, the present invention is not limited to the above embodiments, and improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the present invention should be within the scope of protection of the present invention.

Claims

1. A method for constructing a self-sensing asphalt concrete pavement structure, characterized in that: The following steps are involved: S1: natural mineral aggregates are mixed with wood biomass, and after mechanical stirring, the temperature is raised to 800-1100°C under nitrogen protection, and the temperature is kept for 30-120 minutes to form a graphitized carbon layer. After annealing and screening, a low-resistance aggregate with a surface coated with a continuous graphitized carbon layer and a resistivity of ≤1×10-3Ω·m is obtained; S2: The low-resistance aggregate obtained in S1 is used to replace the conventional aggregate at a mass ratio of 70-90%, combined with asphalt binder and filler, to prepare a conductive asphalt mixture according to the continuous grading requirements; S3: Use the conductive asphalt mixture obtained in S2 for road paving. Under the action of vehicle load, the resistance value of the entire road surface changes in real time due to the change in the contact state between aggregates and the microstructure adjustment of the conductive network. By monitoring the resistance change law, road structure strain monitoring, traffic flow monitoring, and fatigue damage warning are realized, thereby giving the asphalt concrete road structure intelligent self-sensing function.

2. A method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: S3 also includes the setting of an electrode sheet, wherein the electrode sheet is used to be connected to a device for monitoring a resistance change rule, and the setting process of the electrode sheet includes: Two electrodes were placed on both sides of the uncured asphalt concrete specimen. or, After 0.2-0.8 cm of graphite powder was evenly coated on both sides of the cured asphalt concrete specimen, two electrode sheets were placed on the graphite powder.

3. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: In S3, the electrode layout meets the JTG E20-2011 standard to ensure a low-resistance path with the modified aggregate conductive network.

4. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 2, characterized in that: In S3, the device for monitoring the resistance change law is an LCR bridge, and the resistance value change between electrodes is monitored by the LCR bridge at a sampling frequency of ≤100ms: When a vehicle load of 1-100KN is applied, the contact resistance of the graphitized carbon layer fluctuates in the range of 0.1-100Ω, resulting in a sensitivity response of 0.5-5Ω / KN.

5. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 2, characterized in that: In S3, the process of realizing road structure strain monitoring, traffic flow monitoring, and fatigue damage early warning includes: Strain monitoring: Invert the local strain distribution of the pavement through the resistance-stress linear relationship; Traffic sensing: using the resistance fluctuation frequency to identify the number of vehicle passes and axle weight; Damage warning: When the abnormal resistance drift is greater than 15% or the waveform is distorted, it is determined to be the critical point of fatigue crack extension.

6. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: In S1, the woody biomass is selected from at least one of bamboo powder, sawdust, bagasse, cotton fiber, and coconut shell fiber, the carbon content in the woody biomass is ≥40wt%, and after being crushed to 50-300 meshes, it is wrapped on the surface of the natural mineral in a volume ratio of 1:10-1:20 through mechanical stirring.

7. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: In S1, the particle size of the natural mineral aggregate is 2.36-31.5 mm, and the natural mineral aggregate is basalt, granite, limestone or siliceous sandstone with a surface roughness Ra≥50 μm.

8. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: In S1, the process of forming the graphitized carbon layer specifically includes: heating to 800-1100°C at a heating rate of 5-10°C / min, and keeping the temperature for 30-120 minutes to generate a carbonized layer containing 3-10 graphene sheets, with an ID / IG value of ≤0.

25.

9. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 1, characterized in that: In S1, the annealing treatment adopts a gradient cooling process: the temperature is reduced from the pyrolysis temperature to a constant temperature platform of 600-800°C at a rate of 5°C / min and maintained for 30 minutes. During the natural cooling process, the oxygen content is ≤50ppm, and finally a continuous carbonized layer with a thickness of 10-200μm and a thermal conductivity of ≥120W / (m·K) is obtained.

10. The method for constructing a self-sensing asphalt concrete pavement structure according to claim 2, characterized in that: In S1, the electrode is one of copper, stainless steel and graphite with an electrical conductivity greater than 105 S / m.

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