A method for monitoring asphalt pavement strain based on strain sensor group

Abstract

The present invention discloses an asphalt pavement strain monitoring method based on a strain sensor group. Considering that the modulus of pavement materials may be different at different temperatures, which may lead to certain errors in the measurement of a single sensor, a rectangular parallelepiped specimen of asphalt mixture with an embedded strain sensor is used. By externally attaching a strain gauge, under a step-by-step loading mode, the measurement result of the strain sensor is corrected according to the strain data measured by the strain gauge as the actual measurement value, thereby ensuring that the output result of the strain sensor can truly reflect the actual state of the pavement structure. The corrected strain sensors at different temperatures are further embedded in the pavement structure, and the Lagrange interpolation method and the nearest neighbor extrapolation method are used to realize accurate measurement and monitoring of the real strain response of the pavement structure under vehicle loads at any temperature. This method is of great significance for guiding the design of pavement structures, explaining the mechanical failure mechanism of pavements under vehicle loads, and proposing reasonable preventive maintenance plans.

Description

Technical Field

[0001] The present invention relates to the technical field of road structure health monitoring, and in particular to an asphalt pavement strain monitoring method based on a strain sensor group. Background Art

[0002] The repeated action of vehicle loads will cause the gradual accumulation of mechanical damage inside the pavement structure, eventually leading to the occurrence of pavement cracks and other diseases, which directly affects the pavement service performance. Therefore, in order to explain the mechanical failure mechanism of the pavement under vehicle loads, to reasonably design the pavement structure and extend the service life of the road, it is necessary to monitor the mechanical response of the pavement structure under vehicle loads, analyze the dynamic response law of the pavement structure, and then provide a theoretical basis for the design of long-life pavement structures.

[0003] In order to monitor the dynamic response of asphalt pavement structure under vehicle load, strain sensors need to be embedded in the pavement structure. However, with the temperature change, the Young's modulus of asphalt pavement material (i.e., asphalt mixture) will show a large difference. Studies have shown that the modulus of asphalt mixture under low temperature conditions in winter is much greater than the modulus of asphalt mixture under high temperature conditions in summer. The modulus of asphalt mixture shows a large difference due to seasonal temperature changes. In the monitoring of the mechanical response of asphalt pavement structure, it will cause uncoordinated deformation between the embedded strain sensor and the asphalt mixture, and the degree of uncoordinated deformation will be different in different seasons, resulting in a large deviation between the measurement output of the strain sensor and the actual stress state of the pavement structure, affecting the judgment of the actual stress state of the pavement structure, and is not conducive to the design of the pavement structure and the formulation of preventive maintenance decisions. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an asphalt pavement strain monitoring method based on a strain sensor group, comprising the following steps:

[0005] S1. Using asphalt mixture of the same material as the asphalt pavement, n asphalt mixture rectangular parallelepiped specimens are prepared. A strain sensor is embedded in the asphalt mixture rectangular parallelepiped specimen. The strain sensor is buried at the geometric center of the asphalt mixture rectangular parallelepiped specimen, and the measurement direction is set to be consistent with the length direction of the asphalt mixture rectangular parallelepiped specimen;

[0006] S2. Store n rectangular asphalt mixture specimens at different temperatures for 24 hours. The storage temperature of the kth rectangular asphalt mixture specimen is T k , and satisfies T k <T k+1 ;

[0007] S3. Strain gauges are attached to the sides of each asphalt mixture rectangular specimen in the length direction. The two ends of the asphalt mixture rectangular specimen in the length direction are pressurized by step-by-step loading. The measurement data of the strain sensor and strain gauge on each asphalt mixture rectangular specimen are collected. The measurement data of the strain sensor on the kth asphalt mixture rectangular specimen is x k , the measurement data of the strain gauge is y k ;

[0008] S4, using the linear formula y k =a k x k The fitting coefficient a is obtained by fitting the strain gauge measurement data and the strain sensor measurement data on the kth asphalt mixture rectangular specimen by the least squares method. k The value of

[0009] S5. All strain sensors are sequentially buried in the asphalt pavement at intervals along the wheel track in the driving direction, and a temperature sensor is buried at the same depth as the strain sensor.

[0010] S6. When the vehicle load acts, the strain time-history response data of each strain sensor is collected. The strain time-history response data of the kth strain sensor is recorded as ε k (t); Taking the peak value of the strain time history curve as the reference, the strain time history response data in the time period before and after △t is intercepted, and the intercepted strain time history response data is unified from the time 0s to obtain the strain time history response data of the strain sensor with the unified initial time, and the strain time history response data of the kth strain sensor with the unified initial time is recorded as ε k ′(t); multiply the strain time history response data by a k , and obtain the corrected strain time history response data of the kth strain sensor with the unified initial time, denoted as a k ε k '(t); the measured temperature of the temperature sensor is denoted as T;

[0011] S7, determine whether the measured temperature T of the temperature sensor is between T1 and T n If it is between , the Lagrange interpolation method is used to calculate the actual pavement strain time-history response; if it is not between , the nearest neighbor principle is used to calculate the actual pavement strain time-history response.

[0012] The technical solution further defined in the present invention is:

[0013] Furthermore, in step S1, the asphalt pavement includes an upper layer, a middle layer and a lower layer from top to bottom in the vertical direction, and the materials of the upper layer, the middle layer and the lower layer are set to SMA13, AC20 and AC25 respectively, and the material of the asphalt mixture rectangular specimen is set to be the same as the material of the lower layer of the asphalt pavement.

[0014] In the above-mentioned asphalt pavement strain monitoring method based on a strain sensor group, the thickness of the upper layer, middle layer and lower layer are set to 4 cm, 6 cm and 8 cm respectively, and the length, width and height of the asphalt mixture rectangular specimen are set to 30 cm, 10 cm and 10 cm respectively.

[0015] In the above-mentioned asphalt pavement strain monitoring method based on a strain sensor group, in step 2, the number of asphalt mixture rectangular specimens is set to 4, and they are respectively recorded as E1, E2, E3 and E4; the strain sensors implanted in the asphalt mixture rectangular specimens are respectively recorded as S1, S2, S3 and S4; the storage temperatures of the asphalt mixture rectangular specimens are respectively recorded as T1, T2, T3 and T4.

[0016] In the above-mentioned asphalt pavement strain monitoring method based on a strain sensor group, the strain sensors S1 and S2 are both configured as resistive strain sensors, and the strain sensors S3 and S4 are both configured as fiber grating strain sensors.

[0017] In the above-mentioned asphalt pavement strain monitoring method based on strain sensor group, the storage temperatures T1, T2, T3 and T4 of the asphalt mixture rectangular specimens are set to -5°C, 10°C, 30°C and 50°C respectively.

[0018] In the above-mentioned asphalt pavement strain monitoring method based on a strain sensor group, in step S5, the spacing between adjacent strain sensors is set to 0.5m, and the temperature sensors are spaced on one side of all strain sensors along the driving direction, and the spacing between the temperature sensors and adjacent strain sensors is set to 0.5m.

[0019] In the above-mentioned asphalt pavement strain monitoring method based on a strain sensor group, the embedding depth of the strain sensor and the temperature sensor is set to 16 cm from the upper surface of the asphalt pavement.

[0020] In the above-mentioned asphalt pavement strain monitoring method based on strain sensor group, in step S7, the actual pavement strain time history response is calculated as follows:

[0021]

[0022] Among them, ε(t) represents the actual strain time-history response of the pavement.

[0023] The beneficial effects of the present invention are:

[0024] In the present invention, considering that the modulus of pavement materials may be different at different temperatures, which may lead to certain errors in the measurement of a single sensor, a rectangular parallelepiped specimen of asphalt mixture with an embedded strain sensor is used, and a strain gauge is attached externally. In a step-by-step loading mode, the measurement result of the strain sensor is corrected according to the strain data measured by the strain gauge as the actual measurement value, thereby ensuring that the output result of the strain sensor can truly reflect the actual state of the pavement structure. The corrected strain sensor at different temperatures is further embedded in the pavement structure, and the Lagrange interpolation method and the nearest neighbor extrapolation method are used to realize accurate measurement and monitoring of the true strain response of the pavement structure under vehicle loads at any temperature, which is of great significance for guiding the design of pavement structures, explaining the mechanical failure mechanism of pavements under vehicle loads, and proposing reasonable preventive maintenance plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of step-by-step loading of a rectangular parallelepiped specimen of asphalt mixture in an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of the road surface structure and sensor distribution in an embodiment of the present invention;

[0027] Figure 3 is a strain time history response curve diagram measured by the strain sensor in an embodiment of the present invention;

[0028] Figure 4 A unified strain time history response curve diagram of the strain sensor at the initial moment in an embodiment of the present invention;

[0029] Figure 5 A unified corrected strain time history response curve diagram of the strain sensor at the initial moment in an embodiment of the present invention;

[0030] Figure 6 It is a graph showing the actual strain time-history response curve of the pavement structure in the embodiment of the present invention.

[0031] Among them: 1. strain sensor; 2. strain gauge; 3. asphalt mixture rectangular specimen; 4. pressure head for step-by-step loading of asphalt mixture rectangular specimen; 5. upper layer; 6. middle layer; 7. lower layer; 8. loaded tire; 9. resistance strain sensor S1; 10. resistance strain sensor S2; 11. fiber Bragg grating strain sensor S3; 12. fiber Bragg grating strain sensor S4; 13. temperature sensor. DETAILED DESCRIPTION

[0032] The present embodiment provides a method for monitoring asphalt pavement strain based on a strain sensor group, comprising the following steps:

[0033] S1, such as Figure 1 and Figure 2 As shown, the asphalt pavement includes an upper layer 5, a middle layer 6 and a lower layer 7 from top to bottom in the vertical direction, the materials of the upper layer 5, the middle layer 6 and the lower layer 7 are respectively set to SMA13, AC20 and AC25, and the thicknesses of the upper layer 5, the middle layer 6 and the lower layer 7 are respectively set to 4 cm, 6 cm and 8 cm;

[0034] Four asphalt mixture rectangular specimens 3 are prepared using asphalt mixture (AC25) of the same material as the lower layer 7 of the asphalt pavement. The length, width and height of the asphalt mixture rectangular specimen 3 are set to 30 cm, 10 cm and 10 cm respectively. A strain sensor 1 is implanted in the asphalt mixture rectangular specimen 3. The strain sensor 1 is buried at the geometric center of the asphalt mixture rectangular specimen 3, and the measuring direction is set to be consistent with the length direction of the asphalt mixture rectangular specimen 3.

[0035] S2, the four asphalt mixture cuboid specimens 3 are respectively recorded as E1, E2, E3 and E4; the strain sensors 1 implanted in the asphalt mixture cuboid specimens are respectively recorded as S1, S2, S3 and S4, wherein the strain sensors S1 and S2 are both configured as resistive strain sensors, and the strain sensors S3 and S4 are both configured as fiber grating strain sensors;

[0036] The four asphalt mixture rectangular specimens 3 are stored at different temperatures for 24 hours, and the storage temperature of the kth asphalt mixture rectangular specimen 3 is recorded as T k , and satisfies T k <T k+1 In this embodiment, the storage temperatures of the asphalt mixture rectangular specimen 3 are respectively recorded as T1, T2, T3 and T4, and T1, T2, T3 and T4 are respectively set to -5°C, 10°C, 30°C and 50°C.

[0037] S3, such as Figure 2 As shown in FIG. 1 , strain gauges 2 are attached to the sides of each asphalt mixture rectangular parallelepiped specimen 3 in the length direction, and the two ends of the asphalt mixture rectangular parallelepiped specimen 3 in the length direction are pressurized by step-by-step loading. The measurement data of the strain sensor 1 and the strain gauge 2 on each asphalt mixture rectangular parallelepiped specimen are collected. The measurement data of the strain sensor 1 on the kth asphalt mixture rectangular parallelepiped specimen 3 is x k , the measurement data of strain gauge 2 is y k ,Table 1 shows the measurement data of strain sensor 1 and strain gauge 2 in 4 asphalt mixture rectangular specimens 3.

[0038]

[0039] S4, using the linear formula yk =a k x k The fitting coefficient a is obtained by fitting the measurement data of strain gauge 2 and strain sensor 1 on the kth asphalt mixture rectangular specimen 3 using the least squares method. k The values ​​of a1, a2, a3, and a4 are 1.224, 1.798, 1.692, and 2.989, respectively.

[0040] S5, such as Figure 2 As shown, strain sensors S1, S2, S3 and S4 are sequentially buried in the asphalt pavement at the wheel track along the driving direction, and a temperature sensor 13 is buried at the same time. The spacing between adjacent strain sensors 1 is set to 0.5m, and the temperature sensors 13 are spaced on one side of all strain sensors 1 along the driving direction, and the spacing between the temperature sensor 13 and the adjacent strain sensor 1 is set to 0.5m; the burying depth of the temperature sensor 13 is the same as that of the strain sensor 1, and is set to 16cm from the upper surface of the asphalt pavement.

[0041] S6. Use ML66 accelerated loading equipment to load the test road. The wheel load of the loaded tire 8 is 50KN, the moving speed is 4m / s, and the moment when the loaded tire 8 is close to the strain sensor S1 and the horizontal distance is 1.25m is taken as the initial time, and the moment when the loaded tire 8 is far away from the strain sensor S4 and the horizontal distance is 1.25m is taken as the end time. Collect the strain time history response data of each strain sensor 1 (such as Figure 3 As shown), the strain time history response data of the kth strain sensor 1 is recorded as ε k (t);

[0042] Taking each strain time history curve peak as the benchmark, the strain time history response data within the time period of 0.25s before and after is intercepted, and the intercepted strain time history response data is unified from the time of 0s to obtain the strain time history response data of the strain sensor 1 with a unified initial time (such as Figure 4 As shown), the strain time history response data of the kth strain sensor 1 with the same initial time is recorded as ε k ′(t); multiply the strain time history response data by a k , and obtain the corrected strain time history response data of the kth strain sensor 1 with the same initial time (such as Figure 5 shown), denoted as a k ε k '(t); The measured temperature of the temperature sensor 13 is denoted as T, and in this embodiment, T is 23°C.

[0043] S7, determine whether the measured temperature T of the temperature sensor 13 is between T1 and T nIf it is between, the Lagrange interpolation method is used to calculate the actual pavement strain time history response; if it is not, the nearest neighbor principle is used to calculate the actual pavement strain time history response, which is specifically as follows:

[0044]

[0045] Among them, ε k (t) represents the actual strain time-history response of the road surface; since the measurement temperature T of the temperature sensor 13 in this embodiment is 23°C, the actual strain time-history response ε of the road surface is calculated according to the following formula: k (t) is calculated, and the calculation result is as follows Figure 6 As shown,

[0046]

[0047] Among them, ε k (t) represents the actual strain time history response of the pavement.

[0048] Taking into account that the modulus of pavement materials will be different at different temperatures, which will lead to certain errors in the measurement of a single sensor, the asphalt mixture rectangular specimen 3 with the strain sensor 1 embedded is used, and the strain gauge 2 is attached externally. Under the step-by-step loading mode, the measurement result of the strain sensor 1 is corrected according to the strain data measured by the strain gauge 2 as the actual measurement value, ensuring that the output result of the strain sensor 1 can truly reflect the actual state of the pavement structure. The corrected strain sensor 1 at different temperatures is further buried in the pavement structure, and the Lagrange interpolation method and the nearest neighbor extrapolation method are used to achieve accurate measurement and monitoring of the true strain response of the pavement structure under vehicle loads at any temperature. This is of great significance for guiding the design of pavement structures, explaining the mechanical failure mechanism of pavements under vehicle loads, and proposing reasonable preventive maintenance plans.

[0049] In addition to the above embodiments, the present invention may also have other implementation modes. Any technical solution formed by equivalent replacement or equivalent transformation falls within the protection scope required by the present invention.

Claims

1. A method for monitoring asphalt pavement strain based on a strain sensor group, characterized in that: The following steps are included S1. Using asphalt mixture of the same material as the asphalt pavement, n asphalt mixture rectangular parallelepiped specimens are prepared. A strain sensor is embedded in the asphalt mixture rectangular parallelepiped specimen. The strain sensor is buried at the geometric center of the asphalt mixture rectangular parallelepiped specimen, and the measurement direction is set to be consistent with the length direction of the asphalt mixture rectangular parallelepiped specimen; S2. Store n rectangular asphalt mixture specimens at different temperatures for 24 hours. The storage temperature of the kth rectangular asphalt mixture specimen is T k , and satisfies T k <T k+1 ; S3. Strain gauges are attached to the sides of each asphalt mixture rectangular specimen in the length direction. The two ends of the asphalt mixture rectangular specimen in the length direction are pressurized by step-by-step loading. The measurement data of the strain sensor and strain gauge on each asphalt mixture rectangular specimen are collected. The measurement data of the strain sensor on the kth asphalt mixture rectangular specimen is x k , the measurement data of the strain gauge is y k ; S4, using the linear formula y k =a k x k The fitting coefficient a is obtained by fitting the strain gauge measurement data and the strain sensor measurement data on the kth asphalt mixture rectangular specimen by the least squares method. k The value of S5. All strain sensors are sequentially buried in the asphalt pavement at intervals along the wheel track in the driving direction, and a temperature sensor is buried at the same depth as the strain sensor. S6. When the vehicle load acts, the strain time-history response data of each strain sensor is collected. The strain time-history response data of the kth strain sensor is recorded as ε k (t); Taking the peak value of the strain time history curve as the reference, the strain time history response data in the time period before and after Δt are intercepted, and the intercepted strain time history response data are unified from the time 0s to obtain the strain time history response data of the strain sensor with the unified initial time, and the strain time history response data of the kth strain sensor with the unified initial time is recorded as ε′ k (t); multiply the strain time history response data by a k , and obtain the corrected strain time history response data of the kth strain sensor with the unified initial time, denoted as a k ε′ k (t); the measured temperature of the temperature sensor is denoted as T; S7, determine whether the measured temperature T of the temperature sensor is between T1 and T n If between, the Lagrange interpolation method is used to calculate the actual pavement strain time history response; If it is not there, the nearest neighbor principle is used to calculate the actual strain time history response of the pavement; The actual strain time-history response of the pavement is calculated as follows: Among them, ε(t) represents the actual strain time-history response of the pavement.

2. The asphalt pavement strain monitoring method based on a strain sensor group according to claim 1, characterized in that: In step S1, the asphalt pavement includes an upper layer, a middle layer and a lower layer from top to bottom in the vertical direction, and the materials of the upper layer, the middle layer and the lower layer are set to SMA13, AC20 and AC25 respectively. The material of the asphalt mixture rectangular specimen is set to be the same as the material of the lower layer of the asphalt pavement.

3. The asphalt pavement strain monitoring method based on strain sensor group according to claim 2 is characterized in that: The thickness of the upper layer, the middle layer and the lower layer are set to 4 cm, 6 cm and 8 cm respectively, and the length, width and height of the asphalt mixture rectangular specimen are set to 30 cm, 10 cm and 10 cm respectively.

4. The asphalt pavement strain monitoring method based on a strain sensor group according to claim 1, characterized in that: In the step S2, the number of asphalt mixture rectangular specimens is set to 4, and they are respectively recorded as E1, E2, E3 and E4; the strain sensors implanted in the asphalt mixture rectangular specimens are respectively recorded as S1, S2, S3 and S4; the storage temperatures of the asphalt mixture rectangular specimens are respectively recorded as T1, T2, T3 and T4.

5. The asphalt pavement strain monitoring method based on strain sensor group according to claim 4 is characterized in that: The strain sensors S1 and S2 are both configured as resistive strain sensors, and the strain sensors S3 and S4 are both configured as fiber grating strain sensors.

6. The asphalt pavement strain monitoring method based on strain sensor group according to claim 4 is characterized in that: The storage temperatures T1, T2, T3 and T4 of the asphalt mixture rectangular specimens are set to -5°C, 10°C, 30°C and 50°C respectively.

7. The asphalt pavement strain monitoring method based on a strain sensor group according to claim 1, characterized in that: In step S5, the spacing between adjacent strain sensors is set to 0.5 m, and the temperature sensors are spaced apart on one side of all strain sensors along the driving direction, and the spacing between the temperature sensors and adjacent strain sensors is set to 0.5 m.

8. The asphalt pavement strain monitoring method based on strain sensor group according to claim 7 is characterized in that: The embedding depth of the strain sensor and the temperature sensor is set to be 16 cm from the upper surface of the asphalt pavement.

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