Evaluation method for coordinated deformation behavior of embedded sensor and asphalt mixture

Abstract

The invention discloses a method for evaluating the coordinated deformation behavior of an embedded sensor and an asphalt mixture, and aims to solve the problem that a standard and accurate evaluation mode for the coordinated deformation behavior of the embedded sensor and the asphalt mixture does not exist at present. The evaluation method comprises the following steps: acquiring corresponding tire action times when an asphalt mixture rut test piece cracks, corresponding tire action times when a sensor is in a misalignment node and corresponding tire action times when the sensor is in a failure node as evolution evaluation indexes; calculating and evaluating the process of the coordinated deformation behavior between the sensor and the mixture by using the three evolution evaluation indexes; according to the method, the service life of the intelligent sensing structure of the embedded sensor under the conditions of different loads and loading frequencies can be obtained, so that the optimal embedding process and embedding position of the sensor and the mix proportion design or other related key parameters of a mixture matched with the deformation of the sensor can be subsequently determined; accurate data support is provided for the design of a long-service-life and high-precision intelligent road embedded sensing system.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent road perception, and particularly to an evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixture. Background Art

[0002] The accurate perception of road information, especially in the scenario of asphalt pavement, is an important part of modern intelligent transportation systems. It relies on advanced technical means to achieve comprehensive, real-time, and accurate monitoring and diagnosis of road conditions. The accurate perception of road information is the basis for the construction and operation and maintenance of intelligent roads. By deploying sensors inside the road structure, information such as complex and changeable road surface conditions, traffic loads, and traffic flows can be perceived, and the mechanical responses inside the road structure can be continuously sensed. Among them, whether the embedded road sensors can perceive structural information and whether the perceived information is accurate depends on their coordinated deformation performance with the road body mixture. Under the action of loads, the coordinated working state of the two can ensure the good operation of the sensors, the perceived information is true and reliable, which is helpful for the scientific maintenance and repair of roads. Therefore, the good coordinated deformation performance between the embedded sensors and the asphalt mixture is the basis for the long life and high precision of the intelligent road embedded perception function system.

[0003] Currently, the evaluation methods for the coordinated deformation between road embedded sensors and asphalt mixture mainly involve forming large beam specimens with embedded sensors and applying loads using a four-point bending fatigue loading mode. However, the currently adopted four-point bending fatigue evaluation method lacks a unified test standard. The forming of the embedded sensor beam specimens requires specific molds and is relatively complex in operation; there is no corresponding accurate research method for small and medium-sized beam specimens. The main reason is that the service conditions of the embedded sensors in small and medium-sized beam specimens are quite different from the actual situation, making it difficult to reflect the evolution process of the coordinated deformation behavior between the sensors and the mixture, and there is no way to reflect the evolution mode of the coordinated deformation behavior between the sensors and the mixture, nor a standardized evaluation method for the whole process of the coordinated deformation behavior between the sensors and the mixture, resulting in the test results being difficult to serve practical engineering applications. Summary of the Invention

[0004] The present invention provides an evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixture to solve the above problems.

[0005] An evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixture, the evaluation method is to obtain the number of tire action times corresponding to the cracking of the asphalt mixture rut specimen, the number of tire action times corresponding to the sensor misalignment node, and the number of tire action times at the sensor failure node as the evolution evaluation indicators, and use the three evolution evaluation indicators to calculate and evaluate the process of the coordinated deformation behavior between the sensors and the mixture.

[0006] As a preferred solution: The process of obtaining the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node is as follows: Embed strain gauges in asphalt mixture specimens of corresponding dimensions according to the design requirements to form inlaid sensor asphalt mixture specimens. Paste the strain gauges in the strain gauges at predetermined positions at the bottom of the asphalt mixture rut specimen. Place the inlaid sensor asphalt mixture specimen in a wheeled polishing and anti-skid integrated machine. Correspondingly adjust the applied load magnitude and tire rotation speed according to the test requirements. Start the wheeled polishing and anti-skid integrated machine for loading. As the loading continues, the corresponding data acquisition instrument of the strain gauge continuously and one by one obtains the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node. Take the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node as three evolution evaluation indicators.

[0007] As a preferred solution: The process of obtaining the number of load actions corresponding to the evolution law of mechanical response during the loading of the asphalt mixture rut specimen is as follows: According to the recorded inlaid sensor asphalt mixture specimen during the loading process, based on the evolution law of mechanical response and the corresponding number of load actions, evaluate the coordinated deformation behavior between the sensor and the mixture. Change the embedding depth of the strain gauge and the performance of the mixture. Correspondingly repeat multiple times to obtain the relevant data of the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node. Record the evolution of the coordinated deformation behavior between the strain gauge and the mixture under each working condition and the number of load actions at the corresponding nodes, and determine the optimal embedding depth of the sensor and the optimal mixture ratio data.

[0008] As a preferred solution: The numerical acquisition processes of the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are respectively obtained through Formula 1, specifically: In the above formula, represents the number of actions of the tire on the asphalt mixture rut specimen measured actually; R represents the rotation speed of the double-wheel group bearing in the wheeled polishing and anti-skid integrated machine; represents the cumulative action time of the wheeled polishing and anti-skid integrated machine; n represents the number of tires; Calculate the strain data of the strain gauge through Formula 2, specifically: In Formula 2 represents the theoretical value of the strain data measured by the strain gauge, It represents the measured value of the strain data measured by the strain gauge and is calculated through Formula 2 is the error of the strain data of the strain gauge and is used to evaluate the sensing performance of the strain gauge; The cumulative action time of the wheeled polishing and anti-skid integrated machine is calculated through Formula 1 Using the cumulative action time of the wheeled polishing and anti-skid integrated machine The theoretical strain value at the position of the internal sensor of the asphalt mixture rut specimen is calculated as: S in Formula 3 represents the theoretical strain value of the internal sensor of the asphalt mixture rut specimen, that is , is obtained by real-time measurement in the experiment. x represents the action time of the load and is also the cumulative action time of the wheeled polishing and anti-skid integrated machine; D in Formula 4 is the error between the theoretical strain value and the actual value of the internal sensor of the asphalt mixture rut specimen and is used to evaluate the sensing performance of the internal sensor of the asphalt mixture rut specimen.

[0009] As a preferred solution: The number of tire actions at the cracking node of the asphalt mixture rut specimen should be no less than 6,500 times. On this premise, the sensor type and mixture performance adopted meet the basic service requirements. Furthermore, the sensing performance of the strain gauge and the sensing performance of the internal sensor of the asphalt mixture rut specimen are combined for a composite evaluation process. The composite evaluation process is as follows: When is not less than 6,500 times, the calculation result of Y is less than 20%, and at the same time the calculation result of D is less than 10%, it indicates that the error is in a normal state. At this time, the sensing performance of the sensor is good, and the deformation behavior between the sensor and the mixture is in a coordinated deformation state; When is not less than 6,500 times, the calculation result of Y is greater than 20%, and at the same time D is less than 10%, it indicates that the specimen is very likely to have cracked. At this time, the sensing performance of the sensor is relatively good, and the deformation behavior between the sensor and the mixture is in a non-coordinated deformation state; When is not less than 6,500 times, the calculation result of Y is greater than 20%, and at the same time the calculation result of D is greater than 10%, it indicates that the sensing performance of the sensor is poor, reflecting that the deformation behavior between the sensor and the mixture is completely in a non-coordinated deformation state under this condition. When it is accompanied by detecting that the strain of the sensor is greater than 4,000, it indicates that the sensing performance of the sensor fails, and the result is discarded and the detection is restarted.

[0010] Compared with the prior art, the present invention provides an evaluation method for the coordinated deformation behavior of an embedded sensor and an asphalt mixture, having the following beneficial effects: The present invention relates to an evaluation method capable of comprehensively and stage-by-stage evaluating the coordinated deformation behavior of embedded sensors and asphalt mixtures. The indicators before the evaluation process are typical, clear, and comprehensive. Real tires are used for stage-by-stage loading. By obtaining the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the misalignment nodes of the sensors, and the number of tire actions at the failure nodes of the sensors as the evolution evaluation indicators under three typical states, the whole process evaluation of the coordinated deformation behavior of the sensors and the mixture along with the loading trend is completed. The acquisition process in the present invention is close to the actual service conditions of road-embedded sensors. Through the quantitative evaluation of the coordinated deformation behavior of the sensors and the mixture, the service life of the intelligent road perception structure of the embedded sensors under different load magnitudes and loading frequencies is obtained, which is beneficial for subsequent determination of the best embedding process, embedding position of the sensors, and the mixture proportion design or other related key parameters adapted to the sensor deformation, providing accurate data support for the design of a long-life and high-precision intelligent road embedded perception system, playing a promoting role in accurately serving the relevant work in actual projects, and being able to provide accurate and comprehensive guidance for the proposal of road scientific maintenance and repair decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is the front view structural schematic diagram of a wheeled grinding and anti-skid integrated machine; Figure 2 is the side view structural schematic diagram of the cushion block placed in the specimen support groove; Figure 3 is the top view schematic diagram of the protective cover plate; Figure 4 is the strain response time history curve of the asphalt mixture rut specimen with embedded sensors during the loading cycle; Figure 5 is the strain response time history curve of the strain gauge during the loading cycle; Figure 6 is the schematic diagram of the comparison curve of the strain of different specimens changing with time.

[0012] In the figure: 1 - grinding machine body; 2 - anti-skid performance test machine body; 3 - moving workbench; 5 - work base; 6 - workbench support frame; 7 - cushion block; 8 - specimen support groove; 9 - protective cover plate; 9-1 - opening; 9-2 - strip-shaped notch. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0014] Embodiment 1: In combination with Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 and Figure 6 to illustrate this embodiment, the evaluation method for the coordinated deformation behavior between the embedded sensor and the asphalt mixture in this embodiment is to obtain the number of load applications corresponding to the evolution law of the mechanical response during the loading process of the asphalt mixture rut specimen as the evolution evaluation index. Specifically, a comprehensive coverage evaluation can be carried out through three evolution evaluation indexes. The three evolution evaluation indexes are respectively the number of tire applications corresponding to the cracking of the asphalt mixture rut specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications at the sensor failure node. The above three evolution evaluation indexes are obtained by using a wheeled polishing and skid resistance integrated machine. The coordinated deformation behavior between the sensor and the mixture is evaluated according to the calculation results through the number of tire applications corresponding to the cracking of the asphalt mixture rut specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications at the sensor failure node obtained.

[0015] In combination with Figure 1 as shown, the wheeled polishing and skid resistance integrated machine in this embodiment is an existing polishing and skid resistance integrated machine, and its specific structure and working principle are the same as those of the wheeled polishing and skid resistance integrated machine for complex road conditions disclosed in CN112098250B. The wheeled polishing and skid resistance integrated machine includes a polishing machine body 1, a skid resistance performance test machine body 2, a moving workbench 3, a working base 5, and two workbench support frames 6. The moving workbench 3 slides on the working base 5, and the two workbench support frames 6 are arranged at intervals above the working base 5. The polishing machine body 1 and the skid resistance performance test machine body 2 are respectively arranged on the two work support frames 6. The wheeled polishing and skid resistance integrated machine mainly includes two parts: a polishing machine body 1 and a skid resistance performance test machine body 2. The operation mode of the wheeled polishing and skid resistance integrated machine is that the polishing machine body 1 first polishes the asphalt mixture rut specimen. When the set polishing time is reached, the polishing stops. The moving workbench 3 slides the specimen under the skid resistance performance test machine body 2, and then the skid resistance performance test is carried out, and the polishing value of the rut plate under each set time condition is recorded. Other existing wheeled polishing and skid resistance integrated machines can also be replaced. The polishing machine body 1 in the wheeled polishing and skid resistance integrated machine includes a double-wheel group, and the double-wheel group is a test tire that directly acts on the asphalt mixture rut specimen.

[0016] Embodiment 2: This embodiment is a further limitation of Embodiment 1. In this embodiment, before the evaluation method is used for evaluation, three evolution evaluation indexes need to be obtained. The three evolution evaluation indexes are respectively the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node. The process of obtaining the three evolution evaluation indexes is as follows: According to the design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form embedded sensor asphalt mixture specimens. The strain gauges are pasted at predetermined positions at the bottom of the asphalt mixture rut specimen. The embedded sensor asphalt mixture specimens are placed in a wheel-type polishing and skid resistance integrated machine. The applied load and tire rotation speed are adjusted correspondingly according to the test requirements. The wheel-type polishing and skid resistance integrated machine is started for loading. As the loading continues, the data acquisition instrument corresponding to the strain gauge continuously and one by one obtains the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node. The number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node are the three evolution evaluation indexes. The above three evolution evaluation indexes can respectively represent different stage states of the coordinated deformation behavior between the embedded sensor and the asphalt mixture, so as to realize the process of comprehensively evaluating the coordinated deformation behavior between the embedded sensor and the asphalt mixture throughout the whole process.

[0017] In this embodiment, the configuration of the strain gauge is to obtain the strain at the bottom of the embedded sensor rut specimen by pasting the strain gauge, and it is used for the correction of sensor data.

[0018] Embodiment 3: This embodiment is a further limitation of Embodiment 1 or 2. The process of obtaining the number of load actions corresponding to the evolution law of mechanical response during the loading of the asphalt mixture rut specimen in this embodiment is as follows: According to the recorded number of load actions corresponding to the evolution law of mechanical response and the corresponding number of load actions of the embedded sensor asphalt mixture specimen during the loading process, the coordinated deformation behavior between the sensor and the mixture is evaluated. The embedding depth of the strain gauge and the performance of the mixture are changed, and the relevant data of the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node are obtained repeatedly. The evolution of the coordinated deformation behavior between the strain gauge and the mixture and the number of load actions at the corresponding nodes under each working condition are recorded to determine the optimal embedding depth of the sensor and the optimal mixture ratio data.

[0019] Embodiment 4: This embodiment is a further limitation of Embodiment 1, 2 or 3. Combining Figure 3As shown in the figure, in this embodiment, a protective cover plate 9 with a corresponding size is installed on the mobile loading platform to load asphalt mixture rut specimens of different heights and protect the input and output cables of strain gauges and sensors. Among them, the value range of the height adjustment of the asphalt mixture rut specimen by the protective cover plate 9 is 50 - 80 mm.

[0020] Furthermore, the protective cover plate 9 is a PVC plastic plate. The protective cover plate 9 is a rectangular plate body. Two symmetrically arranged openings 9-1 are processed along the thickness direction of the protective cover plate 9. The openings 9-1 are rectangular openings. The axis of symmetry of the two openings 9-1 is the middle axis along the length direction of the protective cover plate 9. A strip-shaped notch 9-2 communicating with the opening 9-1 is also processed on one side of the protective cover plate 9. The strip-shaped notch 9-2 communicates with the opening 9-1 in a one-to-one correspondence to achieve the corresponding deformation protection effect on the input and output cables of the strain gauges and sensors. The processing of the position and the matching and communicating relationship between the strip-shaped notch 9-2 and the opening 9-1 are for the convenience of leading out the wires of the strain gauges.

[0021] Furthermore, the size requirements of the protective cover plate 9 are high. Its corresponding size is 1300 mm in length, 950 mm in width. The shape of the opening 9-1 is a square, and the length and width dimensions of the opening 9-1 are both 300 mm. The length of the strip-shaped notch 9-2 is 325 mm, and the width of the strip-shaped notch 9-2 is 10 mm.

[0022] Specific Embodiment 5: This embodiment is a further limitation of Specific Embodiments 1, 2, 3, or 4. In this embodiment, the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen measured in the experiment, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are not the final measured values. It is also necessary to further determine the measured values based on the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen measured in the experiment, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node in combination with Formula 1, and calculate the theoretical values of the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen by the tire and the theoretical values of the number of tire actions corresponding to the sensor misalignment node respectively; The numerical acquisition processes of the number of tire actions corresponding to the cracking of the asphalt mixture rut specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are respectively obtained through Formula 1, specifically: In the above formula, represents the number of tire actions on the asphalt mixture rut specimen obtained by actual measurement; R represents the rotational speed of the double-wheel group bearings in the wheeled polishing and anti-skid integrated machine; represents the cumulative action time of the wheeled polishing and anti-skid integrated machine; n represents the number of tires; Calculate the strain data of the strain gauge through Formula 2, specifically as follows: In Formula 2 represents the theoretical value of the strain data measured by the strain gauge, represents the measured value of the strain data measured by the strain gauge, calculated through Formula 2 is the error of the strain data of the strain gauge, used to evaluate the sensing performance of the strain gauge; Calculate the cumulative action time of the wheeled polishing and anti-skid machine through Formula 1 Utilize the cumulative action time of the wheeled polishing and anti-skid machine Calculate the theoretical strain value at the position of the internal sensor of the asphalt mixture rut specimen as: S in Formula 3 represents the theoretical strain value of the internal sensor of the asphalt mixture rut specimen, that is , is obtained by real-time measurement in the experiment, x represents the action time of the load, which is also the cumulative action time of the wheeled polishing and anti-skid machine; D in Formula 4 is the error between the theoretical strain value and the actual value of the internal sensor of the asphalt mixture rut specimen, used to evaluate the sensing performance of the internal sensor of the asphalt mixture rut specimen.

[0023] In this embodiment, the load action time x is obtained by conversion through the load action times using Formula 1; S calculated through Formula 3 in this embodiment represents the theoretical value of the current position of the sensor obtained under a certain actual load action times, while the actual value of the position of the internal sensor of the asphalt mixture rut specimen is obtained by real-time experiment.

[0024] Specific Embodiment 6: This embodiment is a further limitation of Specific Embodiment 5. In this embodiment, the number of tire action times at the cracking node of the asphalt mixture rut specimen should be not less than 6500 times. On this premise, the type of sensor and the mixture performance adopted meet the basic service requirements. Furthermore, a composite evaluation process is carried out by combining the sensing performance of the strain gauge and the sensing performance of the internal sensor of the asphalt mixture rut specimen. The composite evaluation process is as follows: When is not less than 6500 times, the calculation result of Y is less than 20%, and at the same time the calculation result of D is less than 10%, it indicates that the error is in a normal state. At this time, the sensing performance of the sensor is good, and the deformation behavior between the sensor and the mixture is in a coordinated deformation state; When Not less than 6500 times, the calculated result of Y is greater than 20%, and at the same time D is less than 10%, indicating that the specimen is very likely to have cracked. At this time, the sensing performance of the sensor is relatively good, and the deformation behavior between the sensor and the mixture is in a non-coordinated deformation state; When Not less than 6500 times, the calculated result of Y is greater than 20%, and at the same time the calculated result of D is greater than 10%, it shows that the sensing performance of the sensor is poor, reflecting that the deformation behavior between the sensor and the mixture is completely in a non-coordinated deformation state. When it is detected that the strain of the sensor is greater than 4000, it indicates that the sensing performance of the sensor fails, and the result is abandoned and the detection is carried out again.

[0025] In this embodiment, the values of 200.11, 4210.94 and other specific values in Formula III are all obtained by fitting according to experimental data. The positions of 200.11 and 4210.94 are the coefficients in the original fitting equation.

[0026] In this embodiment, the theoretical value of the strain gauge in Formula II is calculated by Formula V, specifically: In the above formula, is the theoretical value representing the strain data measured by the strain gauge, represents the cumulative action time of the wheeled polishing and anti-skid integrated machine, and the unit is min.

[0027] Specific Embodiment Seven: Combining Figure 1 、 Figure 2 and Figure 3 to illustrate this embodiment, the specific operation steps of the evaluation method in this embodiment are: Step 1: Embed a strain gauge during the forming process of the asphalt mixture, and form a 300mm * 300mm * 50mm standard asphalt mixture rut specimen embedded with a sensor.

[0028] Step 2: Paste a strain gauge at the bottom of the asphalt mixture rut specimen embedded with a sensor, connect the input and output cables of the strain gauge and the sensor to the data acquisition instrument, and place a protective cover 9 to protect the input and output cables to prevent them from being damaged during the tire rolling process.

[0029] Step 3: Place the asphalt mixture rut specimen embedded with a sensor into the specimen support groove 8 of the wheeled polishing and anti-skid integrated machine, and raise the asphalt mixture rut specimen to achieve bottom voiding. Then adjust the tire height so that it just touches the surface of the asphalt mixture rut specimen. Among them, place a spacer 7 in the specimen support groove 8 to achieve 5mm bottom voiding of the asphalt mixture rut specimen to accelerate its cracking process under repeated loads.

[0030] Among them, the spacer block 7 is preferably made of stainless steel or other materials with the same compressive strength. The size of the stainless steel spacer block 7 is 5 mm thick and 10 mm wide, and the corresponding size of the specimen bracket 8 is 50 mm high and 300 mm wide. The spacer block 7 is a strip-shaped block, and the spacer block 7 is arranged on both sides inside the specimen bracket 8 along the length direction of the specimen bracket 8.

[0031] Step 4: Gradually increase the tire load, observe and record the sensed data of the sensor during the loading process, judge whether the sensor can normally sense the mechanical response inside the structure and whether the sensing is accurate, and evaluate the influence of the sensor embedding process on its survival rate and sensing accuracy based on this, and determine the best embedding process.

[0032] Step 5: Select the applied load size and tire rotation speed. In this step, a real car tire is used for loading, and both the load size and the tire rotation speed can be controlled according to specific operation requirements. Start the equipment for continuous loading, observe and record the sensed data of the bottom strain gauge and the sensor of the asphalt mixture rut specimen, record the number of tire actions when the asphalt mixture rut specimen cracks and the sensor loses accuracy or fails, and use it as an index to determine the coordinated deformation behavior evolution of the embedded sensor and the mixture.

[0033] Step 6: When the strain gauge data suddenly reaches the maximum range, it indicates that the bottom of the asphalt mixture rut specimen has cracked, resulting in the fracture of the strain gauge. Record the tire load action time at this time and calculate the cumulative action number, which is the load action number at the cracking node of the asphalt mixture rut specimen. After continuing to load for a period of time, the sensor data will continue to increase. When it is felt that the data no longer continues to increase and the floating degree is very large, it indicates that the sensor has failed and the sensed data is inaccurate. At this time, stop loading and record the tire load action time at this time. According to the mechanical response evolution law and the corresponding load action number of the embedded sensor rut specimen obtained from the record during the loading process, evaluate the coordinated deformation behavior between the sensor and the mixture. Change the embedding depth of the sensor and the performance of the mixture, and repeat Steps 1 to 6, record the evolution of the coordinated deformation behavior of the embedded sensor and the mixture under each working condition and the load action number of the corresponding nodes, and determine the best embedding depth of the sensor and the best mix design of the mixture.

[0034] In Step 6, the determination of inaccurate sensed data is obtained through the determination of the inaccurate node. The determination process of inaccurate sensed data is that the inaccuracy occurs before the failure. When the sensed strain data grows rapidly in a short period of time but still satisfies a certain growth law, it indicates that the sensor has become inaccurate. Determine the node at the beginning of this change as the inaccurate node. Other structures and connection relationships not mentioned are the same as those in the specific implementation manners one, two, three, four, five, or six.

[0035] Embodiment VIII: This embodiment is a further limitation of Embodiment I, II, III, IV, V, VI or VII. The specific obtaining process of the three evolution evaluation indexes is as follows: Corresponding data for the first typical case: According to the design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form embedded sensor asphalt mixture specimens. The strain gauges in the strain gauges are pasted at predetermined positions at the bottom of the asphalt mixture rut specimens. The embedded sensor asphalt mixture specimens are placed in a wheel-type polishing and anti-skid integrated machine. The applied load and tire rotation speed are adjusted correspondingly according to the test requirements. The applied load is 0.7 MPa and the tire rotation speed is 50 r / min. The wheel-type polishing and anti-skid integrated machine is started for loading. As the loading continues, the data acquisition instrument corresponding to the strain gauge continuously and one by one obtains the tire action times corresponding to the cracking of the asphalt mixture rut specimen, the tire action times corresponding to the sensor misalignment node, and the tire action times corresponding to the sensor failure node as the three evolution evaluation indexes. Specifically, the tire action times corresponding to the cracking of the asphalt mixture rut specimen are 12,332 times, the tire action times corresponding to the sensor misalignment node are 13,450 times, and the tire action times corresponding to the sensor failure node are 15,000 times.

[0036] Embodiment IX: This embodiment is a further limitation of Embodiment I, II, III, IV, V, VI, VII or VIII. The specific obtaining process of the three evolution evaluation indexes is as follows: Corresponding data for the second typical case: According to the design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form embedded sensor asphalt mixture specimens. The strain gauges in the strain gauges are pasted at predetermined positions at the bottom of the asphalt mixture rut specimens. The embedded sensor asphalt mixture specimens are placed in a wheel-type polishing and anti-skid integrated machine. The applied load and tire rotation speed are adjusted correspondingly according to the test requirements. The applied load is 0.4 MPa and the tire rotation speed is 60 r / min. The wheel-type polishing and anti-skid integrated machine is started for loading. As the loading continues, the data acquisition instrument corresponding to the strain gauge continuously and one by one obtains the tire action times corresponding to the cracking of the asphalt mixture rut specimen, the tire action times corresponding to the sensor misalignment node, and the tire action times corresponding to the sensor failure node as the three evolution evaluation indexes. Specifically, the tire action times corresponding to the cracking of the asphalt mixture rut specimen are 17,422 times, the tire action times corresponding to the sensor misalignment node are 19,554 times, and the tire action times corresponding to the sensor failure node are 22,476 times.

[0037] The above data indicate that the data ranges for applying load, tire speed, and obtaining the number of tire actions corresponding to cracking of asphalt mixture rutting specimens, the number of tire actions corresponding to sensor misalignment nodes, and the number of tire actions at sensor failure nodes do not follow a single pattern, and the evaluation method of the present invention can comprehensively and accurately perform corresponding evaluations.

[0038] Specific implementation method 10: This implementation method is a further limitation of specific implementation methods 1, 2, 3, 4, 5, 6, 7, 8 or 9. Figure 4 , Figure 5 and Figure 6 As shown, the evaluation method in this embodiment analyzes the experimental data to form an evaluation curve to obtain the process as follows: After the tire contacts the surface of the asphalt mixture rutting specimen with the embedded sensor and starts loading, the sensing data of the sensor and the strain gauge remain relatively stable at the initial stage of stress. At this time, the sensing data is low and the fluctuation degree is small. As the number of tire load actions increases, the sensing data will gradually increase. When the cumulative number of tire load actions reaches a certain value, cracks will occur at the bottom of the asphalt mixture rutting specimen, causing the strain gauge to break. The sensing data of the strain gauge shows that it has reached the maximum range, but the sensor inside the asphalt mixture rutting specimen has not reached the maximum range at this time and can continue to sense and obtain data. There is also sensor perception inaccuracy between the strain gauge breakage and sensor failure. This is the link where the sensed strain data increases rapidly in a short period of time. The sensor's sensing data is large and there is a large degree of fluctuation, indicating that the sensor now bears part of the tensile force and can no longer coordinate deformation with the asphalt mixture of the road body, and the sensor's perception performance fails.

[0039] In this embodiment Figure 4 and Figure 5 This is a set of experimental results. The tire load size is 0.7MPa, the speed of the polishing machine body 1 double wheel group is 50r / min, and the height of the asphalt mixture rutting specimen with the embedded sensor is 50mm. When the tire load corresponding to the sensing failure node is 15,000 times, it means that the sensor has completely failed. The strain gauge fracture is the uncoordinated deformation, which is the initial starting time node. At this time, the bottom of the asphalt mixture rutting specimen cracks, the strain gauge breaks and reaches the maximum range.

[0040] The specific process of obtaining the evaluation curve in the present invention is as follows: when the height of the asphalt mixture rutting specimen with the built-in sensor is 50 mm, the evaluation method is then used to select the load size and loading rate corresponding to the design requirements to carry out a long-term loading test of 3-5 h, record the strain data of the entire experimental process, and organize the change curve.

[0041] This evaluation curve reflects the variation law of the sensor's sensed data with the increase in the number of loadings within the long-term loading range, and can reflect that there are three stages in the coordinated deformation between the sensor and the road body structure: the stage of coordinated deformation between the sensor and the road body structure, where the sensed data of the sensor is relatively accurate, the overall deformation of the structure is small, and the floating degree of strain is low; the stage of inaccurate sensor sensing, at this time, cracking usually occurs at the bottom of the asphalt mixture rut specimen, resulting in a decrease in the sensing accuracy of the sensor, and the overall deformation of the structure increases sharply; the stage of sensor failure, at this time, the overall deformation of the structure is large and the sensed data fluctuates greatly, indicating that the sensor has completely failed and cannot sense the strain inside the structure, completing the whole-process quantitative evaluation process composed of stages.

[0042] Under the premise that the loading method in the present invention can meet the requirements of relevant specifications, a method for studying the coordinated deformation behavior between the embedded sensor and the asphalt mixture indoors is realized through a standard rut specimen that replaces the road surface structure indoors. The size of the asphalt mixture rut specimen can meet the specification requirements, and indoor loading can be carried out according to different test requirements to analyze the quantitative classification evaluation process of the coordinated deformation behavior between the embedded sensor and different asphalt mixtures.

Claims

1. A method for evaluating the coordinated deformation behavior of an embedded sensor and an asphalt mixture, characterized in that: The evaluation method is to obtain the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node as evolution evaluation indicators, and use the three evolution evaluation indicators to calculate and evaluate the process of coordinated deformation behavior between the sensor and the mixture.

2. The method for evaluating the coordinated deformation behavior of an embedded sensor and an asphalt mixture according to claim 1, characterized in that: The process of obtaining the tire action times corresponding to the cracking of the mixture rutting specimen, the tire action times corresponding to the sensor misalignment node, and the tire action times at the sensor failure node is as follows: According to the design requirements, the strain gauge is buried in the asphalt mixture specimen of corresponding size to form an embedded sensor asphalt mixture specimen, the strain gauge in the strain gauge is pasted at the predetermined position at the bottom of the asphalt mixture rutting specimen, the embedded sensor asphalt mixture specimen is placed in the wheel-type polishing and anti-skid integrated machine, the applied load size and tire speed are adjusted according to the test requirements, the wheel-type polishing and anti-skid integrated machine is started for loading, and as the loading continues, the data acquisition instrument corresponding to the strain gauge continuously and one by one obtains the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node, and the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are used as three evolution evaluation indicators.

3. The method for evaluating the coordinated deformation behavior of an embedded sensor and asphalt mixture according to claim 2, characterized in that: The process of obtaining the corresponding number of load actions in the asphalt mixture rutting specimen during the loading process in combination with the mechanical response evolution law is as follows: according to the recorded mechanical response evolution law and the corresponding number of load actions of the embedded sensor asphalt mixture specimen during the loading process, the coordinated deformation behavior between the sensor and the mixture is evaluated, the buried depth of the strain gauge and the performance of the mixture are changed, and the relevant data of the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are obtained repeatedly, the evolution of the coordinated deformation behavior of the strain gauge and the mixture under each working condition and the number of load actions at the corresponding nodes are recorded, and the optimal buried depth of the sensor and the optimal mix ratio data of the mixture are determined.

4. The method for evaluating the coordinated deformation behavior of an embedded sensor and an asphalt mixture according to claim 1, 2 or 3, characterized in that: The numerical acquisition process of the number of tire actions corresponding to the cracking of the mixture rutting specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions at the sensor failure node are obtained by formula 1, which is specifically: In the above formula, It represents the number of times the tire acts on the asphalt mixture rutting specimen actually measured; R represents the speed of the double wheel bearing in the wheel polishing and anti-skid integrated machine; Indicates the cumulative action time of the wheel polishing and anti-skid integrated machine; n indicates the number of tires; The strain data of the strain gauge is calculated by formula 2, specifically: Formula 2 Represents the theoretical value of the strain data measured by the strain gauge, Represents the actual value of the strain data measured by the strain gauge, calculated by formula 2 is the error of the strain data of the strain gauge, which is used to evaluate the sensing performance of the strain gauge; The cumulative action time of the wheel polishing anti-slip machine is calculated by formula 1 Cumulative action time of the wheel polishing anti-slip machine The theoretical strain value of the asphalt mixture rutting specimen at the location of the sensor is calculated as: The S in formula 3 represents the theoretical strain value of the sensor inside the asphalt mixture rutting specimen, that is, , It is obtained by real-time measurement of the experiment, x represents the action time of the load, which is also the cumulative action time of the wheel polishing and anti-skid integrated machine; D in formula 4 is the error between the theoretical strain value and the actual value of the internal sensor of the asphalt mixture rutting specimen, which is used to evaluate the perception performance of the internal sensor of the asphalt mixture rutting specimen.

5. The method for evaluating the coordinated deformation behavior of an embedded sensor and an asphalt mixture according to claim 4, characterized in that: The number of tire actions on the cracking node of the mixture rutting specimen should be no less than 6500 times. Under this premise, the sensor type and mixture performance used meet the basic service requirements. Then, the sensing performance of the strain gauge is combined with the sensing performance of the internal sensor of the asphalt mixture rutting specimen to conduct a composite evaluation process. The composite evaluation process is as follows: when When the calculation result of Y is less than 20% and the calculation result of D is less than 10% for not less than 6500 times, it indicates that the error is in a normal state. At this time, the sensor has good sensing performance and the deformation behavior between the sensor and the mixture is in a coordinated deformation state. when Not less than 6500 times, the calculated result of Y is greater than 20%, and D is less than 10%, indicating that the specimen is very likely to have cracked. At this time, the sensor's sensing performance is relatively good, and the deformation behavior between the sensor and the mixture is in a non-coordinated deformation state; when When the calculation result of Y is greater than 20% and the calculation result of D is greater than 10% for not less than 6500 times, it indicates that the sensor's perception performance is poor, reflecting that the deformation behavior between the sensor and the mixture under this condition is completely in a non-coordinated deformation state. When the strain of the sensor detected is greater than 4000, it indicates that the sensor's perception performance fails and the result is abandoned and retested.

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