Method for evaluating deformation behavior of in-situ sensor and asphalt mixture

Abstract

The application discloses an evaluation method for the coordinated deformation behavior of an embedded sensor and asphalt mixture, and there is no specification and accurate evaluation method for the coordinated deformation behavior of the embedded sensor and the asphalt mixture at present. The evaluation method is used for obtaining the tire action times corresponding to the cracking of an asphalt mixture rut test piece, the tire action times corresponding to the sensor misalignment node, and the tire action times corresponding to the sensor failure node as evolution evaluation indexes, and the coordinated deformation behavior between the sensor and the mixture is calculated and evaluated by using the three evolution evaluation indexes. The application can obtain the service life of the embedded sensor intelligent sensing structure under different load sizes and loading frequencies, is beneficial to subsequent determination of the best embedding process, embedding position of the sensor and mixture mix design matched with the deformation of the sensor or other related key parameters, and provides accurate data support for the design of a long-service-life and high-precision intelligent road embedded sensing system.

Description

Technical Field

[0001] This invention relates to the field of intelligent road perception technology, specifically to an evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixtures. Background Technology

[0002] Accurate road information perception, especially on asphalt pavements, is a crucial component of modern intelligent transportation systems. It relies on advanced technologies to achieve comprehensive, real-time, and accurate monitoring and diagnosis of road conditions. Accurate road information perception is fundamental to the construction and operation of smart roads. Sensors deployed within the road structure can detect complex and ever-changing road surface conditions, traffic loads, and traffic flow, and continuously sense the mechanical responses within the pavement structure. The accuracy and effectiveness of embedded sensors in perceiving structural information depend on their coordinated deformation performance with the road's aggregate. Under load, this coordinated operation ensures proper sensor function and reliable information, contributing to the scientific maintenance and repair of roads. Therefore, good coordinated deformation performance between embedded sensors and the asphalt mixture is fundamental to achieving long lifespan and high precision in intelligent road embedded sensing systems.

[0003] Current evaluation methods for the coordinated deformation between embedded sensors and asphalt mixtures mainly involve molding large beam specimens with embedded sensors and applying loads using a four-point bending fatigue loading mode. However, the current four-point bending fatigue evaluation method lacks a unified test standard, and molding the embedded sensor beam specimens requires specific molds, making the operation relatively complex. Furthermore, no corresponding precise research method has been developed for small- to medium-sized beam specimens. This is mainly because the service conditions of the embedded sensors in small- to medium-sized beam specimens differ significantly from real-world conditions, making it difficult to reflect the evolution of the coordinated deformation behavior between the sensor and the mixture. There is no method to reflect the evolution of this behavior, nor is there a standardized evaluation method for the entire process of coordinated deformation between the sensor and the mixture, making it difficult to apply the test results to practical engineering applications. Summary of the Invention

[0004] This invention provides an evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixtures to solve the above-mentioned problems.

[0005] An evaluation method for the coordinated deformation behavior of an embedded sensor and asphalt mixture is proposed. The evaluation method involves obtaining 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 corresponding to the sensor failure node as evolution evaluation indicators. The process of calculating and evaluating the coordinated deformation behavior between the sensor and the mixture is then carried out using the three evolution evaluation indicators.

[0006] As a preferred method, the process for obtaining the number of tire applications corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications corresponding to the sensor failure node is as follows:

[0007] According to the design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form asphalt mixture specimens with embedded sensors. The strain gauges are attached to predetermined positions on the bottom of the asphalt mixture rutting specimens. The asphalt mixture specimens with embedded sensors are placed in a wheel-type polishing and anti-skid machine. The applied load and tire speed are adjusted according to the test requirements. The wheel-type polishing and anti-skid machine is started for loading. As the loading continues, the data acquisition instrument corresponding to the strain gauge continuously and sequentially acquires 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 corresponding to the sensor failure node. 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 corresponding to the sensor failure node are used as three evolution evaluation indicators.

[0008] As a preferred option, the process of obtaining the number of load applications corresponding to the mechanical response evolution law of asphalt mixture rutting specimens during loading is as follows: Based on the recorded mechanical response evolution law and the corresponding number of load applications of the embedded sensor asphalt mixture specimens during loading, 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. The relevant data of the number of tire applications corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications 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 applications at the corresponding nodes are recorded under each working condition. The optimal embedding depth of the sensor and the optimal mix proportion data of the mixture are determined.

[0009] As a preferred option: the numerical values ​​of the number of tire applications corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications corresponding to the sensor failure node are obtained by formula 1, specifically as follows: In the above formula, This indicates the actual number of times the tires acted on the asphalt mixture rutting specimen, as measured in actual measurements; R represents the rotational speed of the dual-wheel bearing group in the wheel-type polishing and anti-skid integrated machine. This indicates the cumulative working time of the wheel-type polishing and anti-skid integrated machine; n represents the number of tires.

[0010] The strain data of the strain gauge is calculated using Formula 2, specifically as follows:

[0011] Formula 2 This represents the theoretical value of the strain data measured by the strain gauge. This represents the measured strain data obtained from the strain gauge, calculated using Formula 2. The error in the strain data of the strain gauge is used to evaluate the sensing performance of the strain gauge;

[0012] The cumulative action time of the wheel-type polishing and anti-slip integrated machine can be calculated using Formula 1. Utilizing the cumulative action time of the wheel-type polishing and anti-slip integrated machine The theoretical strain value at the location of the sensor inside the asphalt mixture rutting specimen is calculated as follows: In Formula 3, S represents the theoretical strain value of the sensor inside the asphalt mixture rutting specimen, i.e. , The values ​​are obtained from real-time measurements in the experiment. x represents the duration of the load application, which is also the cumulative application time of the wheel-type polishing and anti-skid integrated machine. In Formula 4, D is the error between the theoretical and actual strain values ​​of the internal sensors of the asphalt mixture rutting specimen, which is used to evaluate the sensing performance of the internal sensors of the asphalt mixture rutting specimen.

[0013] As a preferred option, the number of tire cycles at the cracking nodes of asphalt mixture rutting specimens should be no less than 6500. Under this premise, the type of sensor used and the performance of the mixture meet the basic service requirements. Then, the sensing performance of the strain gauges is combined with the sensing performance of the sensors inside the asphalt mixture rutting specimens for a composite evaluation process. The composite evaluation process is as follows:

[0014] when If the calculation result of Y is less than 20% after no less than 6500 times and the calculation result of D is less than 10%, it indicates that the error is in a normal state. At this time, the sensor's sensing performance is good and the deformation behavior between the sensor and the mixture is in a coordinated deformation state.

[0015] when If the number of tests is not less than 6500, the calculated value of Y is greater than 20%, and D is less than 10%, it indicates 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.

[0016] when If the number of tests is not less than 6500, and the calculated result of Y is greater than 20%, while the calculated result of D is greater than 10%, it indicates that the sensor's sensing performance is poor. This reflects that the deformation behavior between the sensor and the mixture under this condition is completely in a non-coordinated deformation state. When the strain detected by the sensor is greater than 4000, it indicates that the sensor's sensing performance has failed, and the result should be discarded and the test should be repeated.

[0017] Compared with the prior art, the present invention provides an evaluation method for the coordinated deformation behavior of embedded sensors and asphalt mixtures, which has the following beneficial effects:

[0018] This invention provides a method for evaluating the coordinated deformation behavior of embedded sensors and asphalt mixtures throughout the entire process, in stages. The evaluation process begins with typical, clear, and comprehensive indicators. Real tires are used for staged loading. The method uses the number of tire applications corresponding to the cracking of asphalt mixture rutting specimens, the number of tire applications corresponding to the sensor misalignment point, and the number of tire applications corresponding to the sensor failure point as evolution evaluation indicators under three typical states. This completes the full-process evaluation of the coordinated deformation behavior of the sensor and mixture as the loading trend evolves. The acquisition process in this invention closely approximates the actual service conditions of embedded road sensors. By quantitatively evaluating the coordinated deformation behavior of sensors and mixtures, the service life of the embedded sensor smart road sensing structure under different load magnitudes and loading frequencies is obtained. This facilitates the subsequent determination of the optimal sensor embedding process, embedding location, and mixture mix design adapted to sensor deformation, or other relevant key parameters. It provides accurate data support for the design of long-life, high-precision smart road embedded sensing systems, promoting precise services in practical engineering and providing accurate and comprehensive guidance for road scientific maintenance and repair decisions. Attached Figure Description

[0019] Figure 1 A schematic diagram of the main structure of a wheel-type integrated polishing and anti-slip machine;

[0020] Figure 2 A side view of the structure where the pad is placed in the specimen slot;

[0021] Figure 3 This is a top view of the protective cover.

[0022] Figure 4 The strain response time history curve of an asphalt mixture rutted specimen with an embedded sensor during the loading period;

[0023] Figure 5 The strain response time history curve during the strain gauge loading cycle;

[0024] Figure 6 This is a schematic diagram showing the comparison of strain changes over time for different specimens.

[0025] In the diagram: 1-Grinding machine body; 2-Anti-slip performance testing machine body; 3-Moving workbench; 5-Working base; 6-Workbench support frame; 7-Padded block; 8-Specimen tray; 9-Protective cover plate; 9-1-Opening; 9-2-Strip notch. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Specific implementation method one: Combining Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 and Figure 6 This embodiment describes an evaluation method for the coordinated deformation behavior of the embedded sensor and asphalt mixture. The method involves obtaining the number of load applications corresponding to the mechanical response evolution law of the asphalt mixture rutting specimen during loading, which serves as an evolution evaluation index. Specifically, a comprehensive evaluation can be conducted using three evolution evaluation indices: the number of tire applications corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment point, and the number of tire applications corresponding to the sensor failure point. These three evolution evaluation indices are obtained using a wheel-type polishing and anti-skid integrated machine. The number of tire applications corresponding to the cracking of the asphalt mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment point, and the number of tire applications corresponding to the sensor failure point are calculated accordingly. Based on the calculation results, the coordinated deformation behavior between the sensor and the mixture is evaluated.

[0028] Combination Figure 1As shown, the wheel-type polishing and anti-skid integrated machine in this embodiment is an existing polishing and anti-skid integrated machine. Its specific structure and working principle are consistent with the structure and working principle of the wheel-type polishing and anti-skid integrated machine for complex road conditions disclosed in CN112098250B. The wheel-type polishing and anti-skid integrated machine includes a polishing machine body 1, an anti-skid performance testing machine body 2, a movable worktable 3, a working base 5, and two worktable support frames 6. The movable worktable 3 slides on the working base 5. The two worktable support frames 6 are spaced apart and arranged above the working base 5. The polishing machine body 1 and the anti-skid performance testing machine body 2 are respectively arranged on the two worktable support frames 6. The wheel-type grinding and anti-skid integrated machine mainly consists of two parts: a grinding machine body 1 and an anti-skid performance testing machine body 2. The operation of the wheel-type grinding and anti-skid integrated machine is as follows: the grinding machine body 1 first grinds the asphalt mixture rutted specimen. After the set grinding time is reached, grinding stops, and the moving worktable 3 slides the specimen under the anti-skid performance testing machine body 2. Then, the anti-skid performance is tested, and the grinding value of the rutted specimen under each set time condition is recorded. Other existing wheel-type grinding and anti-skid integrated machines can also be used as replacements. The grinding machine body 1 in the wheel-type grinding and anti-skid integrated machine includes a double-wheel set, which serves as the test tire and acts directly on the asphalt mixture rutted specimen.

[0029] Specific Implementation Method Two: This implementation method is a further limitation of Specific Implementation Method One. In this implementation method, the evaluation method requires the acquisition of three evolution evaluation indicators before evaluation. The three evolution evaluation indicators are 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 corresponding to the sensor failure node. The process of acquiring the three evolution evaluation indicators is as follows:

[0030] According to design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form asphalt mixture specimens with embedded sensors. The strain gauges are attached to predetermined positions on the bottom of the asphalt mixture rutting specimens. The asphalt mixture specimens with embedded sensors are placed in a wheel-type polishing and anti-skid machine. The applied load and tire speed are adjusted according to the test requirements. The wheel-type polishing and anti-skid machine is started for loading. As loading continues, the data acquisition instrument corresponding to the strain gauge continuously and sequentially acquires 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 corresponding to the sensor failure node. 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 corresponding to the sensor failure node are the three evolution evaluation indicators. The above three evolution evaluation indicators can respectively represent different stages of the coordinated deformation behavior between the embedded sensor and the asphalt mixture, so as to realize the process of comprehensive evaluation of the coordinated deformation behavior between the embedded sensor and the asphalt mixture.

[0031] In this embodiment, the strain gauges are configured to obtain the strain at the bottom of the rutted specimen with the embedded sensor by attaching the strain gauges, and to be used for the calibration of the sensor data.

[0032] Specific Implementation Method 3: This implementation method is a further limitation of Specific Implementation Method 1 or 2. In this implementation method, the process of obtaining the number of load actions corresponding to the mechanical response evolution law of asphalt mixture rutting specimens during loading is as follows: Based on the recorded mechanical response evolution law and the corresponding number of load actions of the embedded sensor asphalt mixture specimens during loading, 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. 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 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 are recorded under each working condition. The optimal embedding depth of the sensor and the optimal mix proportion data of the mixture are determined.

[0033] Specific Implementation Method Four: This implementation method is a further limitation of Specific Implementation Methods One, Two, or Three, combined with... Figure 3 As shown, in this embodiment, loading of asphalt mixture rutted specimens of different heights is achieved by installing protective cover plates 9 of corresponding sizes on the mobile loading platform, and the input and output cables of strain gauges and sensors are protected. The range of adjustment of the height of the asphalt mixture rutted specimens by the protective cover plates 9 is 50~80mm.

[0034] Furthermore, the protective cover 9 is a PVC plastic sheet, and the protective cover 9 is a rectangular plate. The protective cover 9 has two symmetrically arranged openings 9-1 processed along its thickness direction. The openings 9-1 are rectangular openings, and the axis of symmetry of the two openings 9-1 is the small axis along the length direction of the protective cover 9. One side of the protective cover 9 is also processed with a strip-shaped notch 9-2 that is connected to the openings 9-1. The strip-shaped notch 9-2 and the openings 9-1 are connected in a one-to-one correspondence to achieve the corresponding deformation protection effect for the input and output cables of the strain gauge and sensor. The position processing and connection relationship between the strip-shaped notch 9-2 and the openings 9-1 are to facilitate the wire connection of the strain gauge.

[0035] Furthermore, the protective cover 9 has high dimensional requirements, with corresponding dimensions of 1300mm in length and 950mm in width. The opening 9-1 is square in shape, with both its length and width being 300mm. The strip-shaped notch 9-2 has a length of 325mm and a width of 10mm.

[0036] Specific Implementation Method Five: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, or Four. In this implementation method, the number of tire actions corresponding to the cracking of the asphalt mixture rutted specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node measured in the experiment are not the final measured values. It is necessary to further determine the measured values ​​based on the number of tire actions corresponding to the cracking of the asphalt mixture rutted specimen, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node measured in the experiment, combined with Formula One. The theoretical values ​​of the number of tire actions corresponding to the cracking of the asphalt mixture rutted specimen and the theoretical values ​​of the number of tire actions corresponding to the sensor misalignment node are calculated respectively.

[0037] The numerical values ​​of the number of tire applications corresponding to the cracking of asphalt mixture rutting specimens, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications corresponding to the sensor failure node are obtained by formula 1, as follows: In the above formula, This indicates the actual number of times the tires acted on the asphalt mixture rutting specimen, as measured in actual measurements; R represents the rotational speed of the dual-wheel bearing group in the wheel-type polishing and anti-skid integrated machine. This indicates the cumulative working time of the wheel-type polishing and anti-skid integrated machine; n represents the number of tires.

[0038] The strain data of the strain gauge is calculated using Formula 2, specifically as follows:

[0039] Formula 2 This represents the theoretical value of the strain data measured by the strain gauge. This represents the measured strain data obtained from the strain gauge, calculated using Formula 2. The error in the strain data of the strain gauge is used to evaluate the sensing performance of the strain gauge;

[0040] The cumulative action time of the wheel-type polishing and anti-slip integrated machine can be calculated using Formula 1. Utilizing the cumulative action time of the wheel-type polishing and anti-slip integrated machine The theoretical strain value at the location of the sensor inside the asphalt mixture rutting specimen is calculated as follows: In Formula 3, S represents the theoretical strain value of the sensor inside the asphalt mixture rutting specimen, i.e. , The values ​​are obtained from real-time measurements in the experiment. x represents the duration of the load application, which is also the cumulative application time of the wheel-type polishing and anti-skid integrated machine. In Formula 4, D is the error between the theoretical and actual strain values ​​of the internal sensors of the asphalt mixture rutting specimen, which is used to evaluate the sensing performance of the internal sensors of the asphalt mixture rutting specimen.

[0041] In this embodiment, the load application time x is calculated by converting the number of load applications using Formula 1; in this embodiment, S calculated using Formula 3 represents the theoretical value of the current location of the sensor under a certain number of actual load applications, while the actual value of the sensor location inside the asphalt mixture rutting specimen is obtained in real time through experiment.

[0042] Specific Implementation Method Six: This implementation method is a further limitation of Specific Implementation Method Five. In this implementation method, the number of tire cycles at the cracking node of the asphalt mixture rutting specimen should not be less than 6500. Under this premise, the type of sensor used and the performance of the mixture 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 for a composite evaluation process. The composite evaluation process is as follows:

[0043] when If the calculation result of Y is less than 20% after no less than 6500 times and the calculation result of D is less than 10%, it indicates that the error is in a normal state. At this time, the sensor's sensing performance is good and the deformation behavior between the sensor and the mixture is in a coordinated deformation state.

[0044] when If the number of tests is not less than 6500, the calculated value of Y is greater than 20%, and D is less than 10%, it indicates 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.

[0045] when If the number of tests is not less than 6500, and the calculated result of Y is greater than 20%, while the calculated result of D is greater than 10%, it indicates that the sensor's sensing performance is poor. This reflects that the deformation behavior between the sensor and the mixture under this condition is completely in a non-coordinated deformation state. When the strain detected by the sensor is greater than 4000, it indicates that the sensor's sensing performance has failed, and the result should be discarded and the test should be repeated.

[0046] In this embodiment, the values ​​of 200.11, 4210.94, and other specific values ​​in Formula 3 are obtained by fitting experimental data. The positions of 200.11 and 4210.94 are the coefficients in the original fitted equation.

[0047] In this embodiment, the theoretical strain gauge value in Formula 2 is calculated using Formula 5, specifically:

[0048] In the above formula, To represent the theoretical value of the strain data measured by the strain gauge, This indicates the cumulative working time of the wheel-type polishing and anti-slip integrated machine, in minutes.

[0049] Specific implementation method seven: Combining Figure 1 , Figure 2 and Figure 3 This embodiment describes the specific operational steps of the evaluation method as follows:

[0050] Step 1: During the molding process of asphalt mixture, strain gauges are embedded to form a standard asphalt mixture rutting specimen with embedded sensors, measuring 300mm*300mm*50mm.

[0051] Step 2: Attach strain gauges to the bottom of the asphalt mixture rutting specimen with embedded sensors, connect the input and output cables of the strain gauges and sensors to the data acquisition instrument, and place protective cover plate 9 to protect the input and output cables to prevent them from being damaged during tire rolling.

[0052] Step 3: Place the asphalt mixture rutting specimen with embedded sensor into the specimen tray 8 of the wheel-type polishing and anti-skid integrated machine, and elevate the asphalt mixture rutting specimen to achieve bottom clearance. Then adjust the tire height so that it just contacts the surface of the asphalt mixture rutting specimen. In this step, place a pad 7 in the specimen tray 8 to achieve a 5mm clearance at the bottom of the asphalt mixture rutting specimen to accelerate its cracking process under repeated load.

[0053] The pad 7 is preferably made of stainless steel or other material with equivalent compressive strength. The stainless steel pad 7 is 5mm thick and 10mm wide, and the corresponding dimensions of the specimen support groove 8 are 50mm high and 300mm wide. The pad 7 is a strip-shaped block, and the pad 7 is arranged on both sides of the specimen support groove 8 along the length direction of the specimen support groove 8.

[0054] Step 4: Gradually increase the tire load, observe and record the sensor data during the loading process, determine whether the sensor can normally sense the mechanical response inside the structure and whether the sensing is accurate, and evaluate the impact of the sensor installation process on its survival rate and sensing accuracy, and determine the optimal installation process.

[0055] Step 5: Select the applied load and tire speed. This step uses real car tires for loading. The load and tire speed can be controlled according to specific operating requirements. Start the equipment for continuous loading, observe and record the data of the bottom strain gauges and sensors of the asphalt mixture rutting specimen, record the number of tire applications when the asphalt mixture rutting specimen cracks and the sensors become inaccurate or fail, and use this as an indicator to determine the evolution of the coordinated deformation behavior between the embedded sensor and the mixture.

[0056] Step Six: When the strain gauge data suddenly reaches its maximum range, cracks appear at the bottom of the surface asphalt mixture rutting specimen, causing the strain gauge to break. Record the tire load application time at this point and calculate the cumulative number of applications, which is the number of load applications at the cracking point of the asphalt mixture rutting specimen. After continuing loading for a period of time, the sensor data will continue to increase. When the data stops increasing and fluctuates significantly, the surface sensor has failed, and the sensing data is inaccurate. At this point, stop loading and record the tire load application time. Based on the recorded evolution of the mechanical response of the embedded sensor rutting specimen during the loading process and the corresponding number of load applications, evaluate the coordinated deformation behavior between the sensor and the mixture. Change the sensor embedding depth and the performance of the mixture, and repeat steps one to six, recording the evolution of the coordinated deformation behavior between the embedded sensor and the mixture under each working condition and the number of load applications at the corresponding points, to determine the optimal sensor embedding depth and the optimal mix design of the mixture.

[0057] In step six, the determination of sensor data inaccuracy is based on identifying the inaccuracy node. The process for determining sensor data inaccuracy is as follows: before failure, if the sensed strain data increases rapidly in a short period of time but still follows a certain growth pattern, it indicates that the sensor has become inaccurate. The node at the very beginning of this change is identified as the inaccuracy node. Other unmentioned structures and connections are the same as in specific implementation methods one, two, three, four, five, or six.

[0058] Specific Implementation Method Eight: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, Five, Six, or Seven. The specific process for obtaining the three evolution evaluation indicators is as follows:

[0059] The corresponding data for the first typical case:

[0060] According to the design requirements, strain gauges were embedded in asphalt mixture specimens of corresponding sizes to form asphalt mixture specimens with embedded sensors. The strain gauges were then attached to predetermined positions on the bottom of the asphalt mixture rutting specimens. The asphalt mixture specimens with embedded sensors were placed in a wheel-type polishing and anti-skid machine. The applied load and tire speed were adjusted according to the test requirements. The applied load was 0.7 MPa, and the tire speed was 50 r / min. The wheel-type polishing and anti-skid machine was started for loading. As the loading continued, the data acquisition instrument corresponding to the strain gauges continuously and sequentially acquired three evolution evaluation indicators: 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 corresponding to the sensor failure node. Specifically, the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen was 12,332, the number of tire actions corresponding to the sensor misalignment node was 13,450, and the number of tire actions corresponding to the sensor failure node was 15,000.

[0061] Specific Implementation Method Nine: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, Five, Six, Seven, or Eight. The specific process for obtaining the three evolution evaluation indicators is as follows:

[0062] The corresponding data for the second typical case:

[0063] According to the design requirements, strain gauges were embedded in asphalt mixture specimens of corresponding sizes to form asphalt mixture specimens with embedded sensors. The strain gauges were then attached to predetermined positions on the bottom of the asphalt mixture rutting specimens. The asphalt mixture specimens with embedded sensors were placed in a wheel-type polishing and anti-skid machine. The applied load and tire speed were adjusted according to the test requirements. The applied load was 0.4 MPa, and the tire speed was 60 r / min. The wheel-type polishing and anti-skid machine was started for loading. As the loading continued, the data acquisition instrument corresponding to the strain gauges continuously and sequentially acquired three evolution evaluation indicators: 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 corresponding to the sensor failure node. Specifically, the number of tire actions corresponding to the cracking of the asphalt mixture rutting specimen was 17,422, the number of tire actions corresponding to the sensor misalignment node was 19,554, and the number of tire actions corresponding to the sensor failure node was 22,476.

[0064] The above data shows that the range of data for applied load, tire speed, and the number of tire actions corresponding to the cracking of asphalt mixture rutted specimens, the number of tire actions corresponding to the sensor misalignment node, and the number of tire actions corresponding to the sensor failure node are not subject to a single rule. The evaluation method of this invention can provide a comprehensive and accurate assessment of these factors.

[0065] Specific Implementation Method Ten: This implementation method is a further limitation of Specific Implementation Methods One, Two, Three, Four, Five, Six, Seven, Eight, or Nine, combined with... Figure 4 , Figure 5 and Figure 6 As shown, the process of obtaining the evaluation curve after analyzing the experimental data in this embodiment is as follows:

[0066] After the tire contacts the surface of the asphalt mixture rutting specimen with embedded sensors and loading begins, the sensing data from both the sensors and strain gauges remain relatively stable in the initial stage of stress, with low data and minimal fluctuation. As the number of tire load applications increases, the sensing data gradually increases. When the cumulative number of tire load applications reaches a certain value, cracks will appear at the bottom of the asphalt mixture rutting specimen, leading to strain gauge breakage. The strain gauge's sensing data shows that it has reached its maximum range, but the sensor inside the asphalt mixture rutting specimen has not yet reached its maximum range and can continue to sense and acquire data. Between strain gauge breakage and sensor failure, there is a period of sensor inaccuracy, which is the point where the sensed strain data increases rapidly in a short period of time. The sensor's sensing data is large and fluctuates significantly, indicating that the sensor is now bearing part of the tensile load and can no longer coordinate with the deformation of the asphalt mixture itself, resulting in sensor failure.

[0067] In this embodiment Figure 4 and Figure 5 This is a set of experimental results. The tire load was 0.7 MPa, the rotation speed of the dual-wheel set of the polishing machine was 50 r / min, and the height of the asphalt mixture rutting specimen with embedded sensor was 50 mm. When the tire load applied at the sensing failure point reached 15,000 cycles, it indicated that the sensor had completely failed. The strain gauge fractured due to uncoordinated deformation, which is the initial time point. At this time, cracks appeared at the bottom of the asphalt mixture rutting specimen, the strain gauge fractured, and the maximum range was reached.

[0068] The specific process for obtaining the evaluation curve in this invention is as follows: when the height of the molded asphalt mixture rutting specimen with embedded sensor is 50mm, the evaluation method is then used to select the load size and loading rate corresponding to the design requirements and conduct a long-term loading test for 3-5 hours. The strain data of the entire experimental process are recorded and the change curve is obtained.

[0069] This evaluation curve reflects the changing pattern of sensor data with increasing loading cycles over a long-term loading range. It demonstrates that the coordinated deformation between the sensor and the road structure exists in three stages: In the coordinated deformation stage, the sensor data is relatively accurate, the overall structural deformation is small, and the strain fluctuation is low; in the sensor inaccuracy stage, cracks typically appear at the bottom of the asphalt mixture rutting specimen, leading to reduced sensor accuracy and a sharp increase in overall structural deformation; in the sensor failure stage, the overall structural deformation is large, and the sensor data fluctuates significantly, indicating that the sensor has completely failed and cannot sense the internal strain of the structure. This completes the phased, fully quantitative evaluation process.

[0070] The loading method in this invention meets the relevant specifications and is a method for studying the coordinated deformation behavior of embedded sensors and asphalt mixtures indoors. It is achieved by using standard rutting specimens that replace road surface structures indoors. The size of the asphalt mixture rutting specimens meets the specifications. Indoor loading can be carried out according to different test requirements to analyze the quantitative classification and evaluation process of the coordinated deformation behavior between embedded sensors and different asphalt mixtures.

Claims

1. A method for evaluating the deformation behavior of in-sensor coordination with asphalt mixture, characterized in that: The evaluation method involves obtaining 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 corresponding to the sensor failure node as evolution evaluation indicators. The process of coordinating deformation behavior between the sensor and the mixture is calculated and evaluated using the three evolution evaluation indicators. According to the design requirements, strain gauges are embedded in asphalt mixture specimens of corresponding sizes to form asphalt mixture specimens with embedded sensors. The strain gauges in the strain gauges are pasted at predetermined positions on the bottom of the asphalt mixture rutting specimens. The asphalt mixture specimens with embedded sensors are then placed in a wheel-type polishing and anti-skid integrated machine. represents the number of passes of the tire on the asphalt mixture rut specimen actually measured; represents the cumulative action time of the wheel-type polishing and slip-resistant all-in-one machine; The error of the strain data of the strain gauge is used to evaluate the sensing performance of the strain gauge. The error between the theoretical and actual strain values ​​of the internal sensors of the asphalt mixture rutting specimens is used to evaluate the sensing performance of the internal sensors of the asphalt mixture rutting specimens. Error of strain data of strain gauges Error of the theoretical strain value and the actual value of the internal sensor of the asphalt mixture rut specimen and the actual number of times of the tire acting on the asphalt mixture rut specimen measured are calculated by the cumulative action time of the wheel-type polishing and anti-skid integrated machine ​ Under the premise that the number of tire cycles at the cracking node of the asphalt mixture rutting specimen should not be less than 6500, the sensor type and mixture performance should meet the service requirements. Then, the sensing performance of the strain gauges should be combined with the sensing performance of the internal sensors of the asphalt mixture rutting specimen for a composite evaluation process.

2. The method for evaluating the coordinated deformation behavior of the embedded sensor and asphalt mixture according to claim 1, characterized in that the asphalt The process for obtaining the number of tire applications corresponding to the cracking of the mixture rutting specimen, the number of tire applications corresponding to the sensor misalignment node, and the number of tire applications corresponding to the sensor failure node is as follows: According to the test requirements, the applied load and tire speed were adjusted accordingly. The wheel-type polishing and anti-skid machine was started for loading. As the loading continued, the data acquisition instrument corresponding to the strain gauge continuously and one by one acquired 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 corresponding to the sensor failure node. 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 corresponding to the sensor failure node were used as three evolution evaluation indicators.

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

4. The evaluation method for the coordinated deformation behavior of an embedded sensor and asphalt mixture according to claim 1, 2, or 3, characterized in that: asphalt... The numerical values ​​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 corresponding to the sensor failure node are obtained by formula 1, as follows: （1） In the above formula, n represents the number of tires; and n represents the number of tires. The strain data of the strain gauge is calculated using Formula 2, specifically as follows: （2） Theoretical value of strain data measured by strain gauge Theoretical value of strain data measured by strain gauge The error of strain data of strain gauge calculated by Formula Two The error of strain data of strain gauge calculated by Formula Two The cumulative action time of the wheel-type polishing and anti-skid integrated machine is calculated by formula one The cumulative action time of the wheel-type polishing and anti-skid integrated machine is calculated by formula one The theoretical strain value of the position of the internal sensor of the asphalt mixture rut test piece is calculated as （3） （4） In Formula 3, S represents the theoretical strain value of the sensor inside the asphalt mixture rutting specimen, i.e. , The measurements were obtained in real time during the experiment. This indicates the duration of the load application, which is also the cumulative application time of the wheel-type polishing and anti-skid integrated machine.

5. The method for evaluating the coordinated deformation behavior of the embedded sensor and asphalt mixture according to claim 4, characterized in that: The tire action times of the cracking node of the asphalt mixture rut test piece should not be less than 6500 times, the sensor type and the mixture performance meet the service requirements, and then the sensing performance of the strain gauge and the sensing performance of the internal sensor of the asphalt mixture rut test piece are combined for composite evaluation process: when If the calculation result of Y is less than 20% after no less than 6500 times and the calculation result of D is less than 10%, it indicates that the error is in a normal state. At this time, the sensor's sensing performance is good and the deformation behavior between the sensor and the mixture is in a coordinated deformation state. when If the number of tests is not less than 6500, the calculated value of Y is greater than 20%, and D is less than 10%, it indicates that the specimen has a probability of cracking. 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 If the number of tests is not less than 6500, and the calculated value of Y is greater than 20%, while the calculated value of D is greater than 10%, it indicates that the sensor's sensing performance is poor, and the deformation behavior between the sensor and the mixture is completely in a non-coordinated deformation state. When the strain value of the sensor detected is greater than 4000, it indicates that the sensor's sensing performance has failed, and the result should be discarded and the test should be repeated.

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