Device and method for detecting thickness of surface layer of asphalt pavement based on coplanar capacitance

Abstract

The invention discloses an asphalt pavement surface thickness detection device and method based on coplanar capacitance, and the method comprises the steps: firstly constructing an annular coplanar capacitance sensor simulation model, selecting two evaluation indexes: sensitivity and maximum penetrable depth, carrying out the performance optimization of an annular coplanar capacitance sensor through employing a response surface method, and carrying out the detection of the thickness of an asphalt pavement surface layer; determining structural parameters of the sensor electrode plate; then, the optimized annular coplanar capacitance sensor is used for obtaining capacitance values of target asphalt pavement surface layers with different thicknesses, and a fitting curve of the asphalt pavement output capacitance and the asphalt surface layer thickness is established; and finally, measuring the target asphalt pavement by using a measuring device, and determining the thickness of the surface layer of the measured asphalt pavement according to the obtained capacitance. The annular coplanar capacitive sensor optimization method provided by the invention has the advantages of high stability, high accuracy, high universality and the like; the method for measuring the thickness of the surface layer of the asphalt pavement has the advantages of high detection precision, high efficiency, real-time performance, low cost and the like.

Description

Technical Field

[0001] The present invention relates to the field of coplanar capacitance sensor detection, and in particular to a device and method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance. Background Art

[0002] Asphalt pavement has become the main pavement form in my country due to its easy construction and maintenance, comfortable driving, and low noise. New asphalt pavement will have a large range of initial damage within 1 to 3 years after operation. From the perspective of construction quality, insufficient thickness of the surface layer or excessive thickness variation aggravates the occurrence of initial damage. Due to the insufficient thickness of the asphalt pavement, the road cannot effectively bear the vehicle load, and it is prone to settlement, dents or rutting. Excessive thickness variation will cause stress concentration, aggravating the damage of the surface layer. Therefore, it is particularly important to detect the thickness of the surface layer of the newly built asphalt road.

[0003] At present, the main methods for measuring the thickness of asphalt pavement surface layer are destructive testing and non-destructive testing. Destructive testing is represented by the coring method, such as the invention application CN118049953A discloses a road construction asphalt pavement thickness measurement component. Although this method can ensure the integrity of the asphalt pavement core sample and can more intuitively see the asphalt surface structure, it will destroy the pavement structure. At the same time, the small number of cores is not representative and is not suitable for large-area pavement thickness detection. Non-destructive testing is mainly based on ground penetrating radar. Although this method has the advantages of high detection efficiency and large-area detection, its detection accuracy mainly depends on the subjective judgment of the radar waveform, and it has the disadvantages of high cost and great environmental impact. Summary of the invention

[0004] In view of the above problems, the present invention discloses a device and method for detecting the surface thickness of an asphalt pavement based on coplanar capacitance. By using a size-optimized annular coplanar capacitance sensor, asphalt pavement surface layers of different thicknesses are detected, and a relationship curve between capacitance and asphalt surface layer thickness is fitted. Then, the target road surface is measured, and the surface thickness of the target road surface is obtained according to the relationship curve and the capacitance value, thereby realizing the detection of the surface thickness of the asphalt pavement in a non-destructive state of the asphalt pavement.

[0005] The technical solution provided by the present invention is: a method for optimizing the size of an electrode plate of a concentric and coplanar capacitive sensor, and the specific optimization steps are as follows:

[0006] 1) Using simulation software, establish simulation models of annular coplanar capacitive sensors and asphalt pavement surface layers with different structural parameters;

[0007] 2) Under the annular coplanar capacitive sensors with different structural parameters, the thickness of the asphalt pavement surface layer is changed and the capacitance value is output;

[0008] 3) The maximum penetration depth and capacitance sensitivity of the annular coplanar capacitive sensor were selected as performance optimization indicators, and the electrode plate structure size was selected as the influencing factor to conduct a single factor analysis;

[0009] 4) Select the structural parameter range of the annular coplanar capacitive sensor after single factor analysis, conduct response surface design experiments, perform variance and response surface analysis based on the experimental results, and output the size of the annular coplanar capacitive sensor with optimal performance.

[0010] Furthermore, the maximum penetration depth capacitance value calculation formula is:

[0011] C d =0.97×(C max -C0)+C0

[0012] In the formula, C d is the output capacitance value of the sensor when the maximum penetration depth is d, C0 is the capacitance value output by the sensor in the air, C max It is the maximum capacitance value output by the sensor as the thickness of the asphalt surface layer increases.

[0013] Furthermore, the capacitance sensitivity is calculated according to the following formula:

[0014] δ=ΔC / Δd

[0015] In the formula, δ is the sensitivity, △C is the change in capacitance, and △d is the thickness of the asphalt surface layer.

[0016] Furthermore, the structural parameters include: R1 is the radius of the excitation electrode, R2 is the inner radius of the receiving electrode, and R3 is the outer radius of the receiving electrode; the relationship between the structural parameters and the maximum penetrable thickness and sensitivity is:

[0017] The capacitance sensitivity gradually increases with the increase of the radius of the excitation electrode, the capacitance value is positively correlated with the sensitivity, and the maximum penetrable depth decreases with the increase of the radius of the excitation electrode; the capacitance sensitivity gradually decreases with the increase of the inner radius of the receiving electrode, and the maximum penetrable depth increases with the increase of the inner radius of the receiving electrode; with the change of the outer radius of the receiving electrode, the change of the capacitance value and the sensitivity is not obvious, and the maximum penetrable depth increases with the increase of the outer radius of the receiving electrode.

[0018] An electrode plate of a concentric and coplanar capacitance sensor is optimized by using the size optimization method.

[0019] Furthermore, the electrode plates are respectively a circular electrode plate and an annular electrode plate, the circular electrode plate serves as an excitation electrode, and the annular electrode plate serves as a receiving electrode.

[0020] A device for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance comprises the electrode plate; it also comprises: a substrate for the electrode plate to be attached, an electrode plate shielding layer arranged at the bottom of the substrate, and a substrate protection layer outside the shielding layer.

[0021] A method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, using the detection device described in claim 4 for detection, and the specific steps are as follows:

[0022] Select the target asphalt pavement to be tested and form asphalt pavements of different thicknesses;

[0023] The output capacitance of the asphalt pavement surface layers of different thicknesses is obtained by measuring with a thickness detection device;

[0024] The output capacitance data is processed to fit the relationship curve between the output capacitance and the asphalt surface thickness under the target asphalt pavement;

[0025] For the target asphalt pavement to be tested, the capacitance is measured using a thickness detection device, and the thickness of the surface layer of the asphalt pavement to be tested is determined based on the relationship curve between the obtained capacitance value and the fitting.

[0026] The present invention proposes a device and method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, which has the following beneficial effects compared with the existing methods:

[0027] (1) The multi-factor optimization method of the annular coplanar capacitive sensor proposed in the present invention can comprehensively consider the capacitance sensitivity and maximum penetration depth of the annular coplanar capacitive sensor to obtain the electrode plate size of the annular coplanar capacitive sensor with the best performance.

[0028] (2) The method of measuring asphalt pavement using an annular coplanar capacitive sensor proposed in the present invention establishes a relationship curve between asphalt surface layers of different thicknesses and capacitance values, and then calculates the thickness of the pavement surface layer based on the capacitance value measured on the target asphalt pavement and the relationship curve. This method has the advantages of non-destructive testing, does not require destruction of the pavement structure, and has the advantages of high detection efficiency and high accuracy.

[0029] (3) The annular coplanar capacitive sensor proposed in the present invention can be assembled with a detection vehicle to obtain real-time data and realize the measurement of the surface thickness of a large-area asphalt pavement. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a simulation model diagram of an annular coplanar capacitive sensor and an asphalt pavement according to an embodiment of the present invention.

[0031] Figure 2 1 is a trend diagram of the capacitance value and capacitance sensitivity output by the annular coplanar capacitance sensor when R1 changes in an embodiment of the present invention.

[0032] Figure 3 This is a trend diagram of the maximum penetration depth of the annular coplanar capacitive sensor under the change of R1 in an embodiment of the present invention.

[0033] Figure 4 This is a trend diagram of the capacitance value and capacitance sensitivity output by the annular coplanar capacitance sensor when R2 changes in an embodiment of the present invention.

[0034] Figure 5 This is a trend diagram of the maximum penetration depth of the annular coplanar capacitive sensor under the change of R2 in an embodiment of the present invention.

[0035] Figure 6 This is a trend diagram of the capacitance value and capacitance sensitivity output by the annular coplanar capacitance sensor when R3 changes in an embodiment of the present invention.

[0036] Figure 7 This is a trend diagram of the maximum penetration depth of the annular coplanar capacitive sensor under the variation of R3 in an embodiment of the present invention.

[0037] Figure 8 This is a 3D diagram of the interactive effect of R1 and R2 on capacitor sensitivity under multi-factor analysis according to an embodiment of the present invention.

[0038] Fig. 9 This is a 3D diagram of the interactive effects of R1 and R3 on the maximum penetrable depth under multi-factor analysis according to an embodiment of the present invention.

[0039] Fig.10 This is a distribution diagram of actual and predicted capacitance sensitivity values ​​under multi-factor analysis according to an embodiment of the present invention.

[0040] Fig.11 This is a distribution diagram of the actual value and predicted value of the maximum penetrable depth under multi-factor analysis of an embodiment of the present invention.

[0041] Fig.12 This is a structural diagram of an annular coplanar capacitive sensor according to an embodiment of the present invention.

[0042] Fig.13 This is a fitting curve of the PAC-13 asphalt surface layer thickness and capacitance in an embodiment of the present invention.

[0043] In the figure: 1.1-circular excitation electrode, 1.2-annular receiving electrode, 1.3-asphalt pavement surface layer, 1.4-asphalt pavement base layer, 1.5-substrate, 1.6-electrode plate shielding layer, 1.7-substrate. DETAILED DESCRIPTION

[0044] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0045] This embodiment provides a device and method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance. The detection device is a ring-shaped coplanar capacitance sensor. Fig.12 The structure includes: a group of concentric and coplanar electrode plates, a substrate 1.5 to which the electrode plates are attached, an electrode plate shielding layer 1.6 arranged at the bottom of the substrate, and a substrate protection layer 1.7 outside the shielding layer; the concentric and coplanar electrode plates include a circular excitation electrode plate 1.1 and an annular receiving electrode plate 1.2.

[0046] The base plate and the substrate are made of glass fiber board.

[0047] Among them, the size optimization method of the concentric and coplanar electrode plates is as follows:

[0048] 1) Using COMSOL Multiphysics simulation software, establish simulation models of annular coplanar capacitive sensors and asphalt pavement surface layers with different structural parameters;

[0049] 2) Under the annular coplanar capacitive sensors with different structural parameters, the thickness of the asphalt pavement surface layer is changed and the Maxwell capacitance value is output;

[0050] 3) The maximum penetration depth and capacitance sensitivity of the annular coplanar capacitive sensor were selected as performance optimization indicators, and the electrode plate structure size was selected as the influencing factor to conduct a single factor analysis;

[0051] 4) Select the structural parameter range of the annular coplanar capacitive sensor after single factor analysis, use the Box-Behnken Design method of Design-expert software to conduct response surface design experiments, perform variance and response surface analysis based on the experimental results, and output the size of the annular coplanar capacitive sensor with optimal performance.

[0052] The simulation model establishment described in step 1) comprises the following steps:

[0053] Select the electrostatic physics field, add a steady-state study, input the sensor structure dimensions, assign the sensor material, assign the excitation electrode voltage, divide the grid, start the study, perform post-processing, and output the Maxwell capacitance value.

[0054] The different structural parameters are R1, R2, and R3, where R1 is the radius of the excitation electrode, R2 is the inner radius of the receiving electrode, and R3 is the outer radius of the receiving electrode.

[0055] Step 2) in which the thickness of the asphalt pavement surface layer is changed, with the thickness ranging from zero to infinity, until the output Maxwell capacitance value no longer changes;

[0056] The maximum penetration depth capacitance value described in step 3) is calculated according to the following formula:

[0057] Cd =0.97×(C max -C0)+C0

[0058] In the formula, C d is the output capacitance value of the sensor when the maximum penetration depth is d, C0 is the capacitance value output by the sensor in the air, C max It is the maximum capacitance value output by the sensor as the thickness of the asphalt surface layer increases.

[0059] The capacitance sensitivity described in step 3) is calculated according to the following formula:

[0060] δ=ΔC / Δd

[0061] In the formula, sensitivity δ is defined as the ratio of the change in capacitance △C to the thickness of the asphalt surface layer △d.

[0062] The present invention discloses a method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, which uses an optimized annular coplanar capacitance sensor for detection, and comprises the following steps:

[0063] 1) Select the target asphalt pavement to be tested, and form asphalt pavements of different thicknesses according to the same asphalt mixture mineral gradation table;

[0064] 2) Performing thickness detection using an annular coplanar capacitive sensor (thickness detection device) assembled with the sensor electrode plates obtained by the above-mentioned size optimization method to obtain output capacitance of asphalt pavement surface layers of different thicknesses;

[0065] 3) Processing the output capacitance data to fit the relationship curve between the output capacitance and the asphalt surface thickness under the target asphalt pavement;

[0066] 4) Select the target asphalt pavement to be tested, use the annular coplanar capacitance sensor (thickness detection device) to measure the capacitance, and determine the thickness of the surface layer of the asphalt pavement to be tested based on the relationship curve between the obtained capacitance value and the fitting.

[0067] The capacitance output in step 2) is obtained using a digital bridge LCR instrument.

[0068] Example

[0069] Using COMSOL Multiphysics simulation software, a simulation model of annular coplanar capacitive sensor with different structural parameters R1, R2, and R3 is established. Figure 1 , output Maxwell capacitance value;

[0070] The maximum penetrable depth and capacitance sensitivity of the annular coplanar capacitive sensor were selected as performance optimization indicators, and the electrode plate structure dimensions R1, R2, and R3 were selected as influencing factors. Each factor was set at 5 levels, and a single factor experiment was carried out to explore the influence of the changes of R1, R2, and R3 on the maximum penetrable thickness d (mm) and sensitivity (pF / mm).

[0071] Table 1 Single factor factors and levels

[0072] R1 / mm R2 / mm R3 / mm 50 90 110 60 100 120 70 110 130 80 120 140 90 130 150

[0073] The study found that the capacitance sensitivity gradually increases with the increase of R1, the capacitance value is positively correlated with the sensitivity, and the maximum penetration depth decreases with the increase of R1. Figure 2 and Figure 3 .

[0074] The study found that the capacitance sensitivity gradually decreases with the increase of R2, and the maximum penetration depth increases with the increase of R2. Figure 4 and Figure 5 .

[0075] The study found that, unlike the changes in R1 and R2, the changes in capacitance and sensitivity under the change of R3 were not obvious, but only slightly increased. The maximum penetration depth increased with the increase of R3. Figure 6 and Figure 7 .

[0076] Further research shows that in order to ensure better sensitivity, the R1 variation range is 70-80mm, and the R2 variation range is 100-110mm. Since the change of R3 does not significantly change the capacitance sensitivity of the annular coplanar capacitive sensor, the maximum penetration depth can be used as the only evaluation indicator under the change of R3, which is 140-150mm.

[0077] According to the above single-factor experimental results, three variables, R1 (70-80mm), R2 (100-110mm), and R3 (140-150mm), were selected. Capacitive sensitivity Y1 and maximum penetrable depth Y2 were used as response indicators. Based on the Box-Behnken response surface design method, a three-factor three-level experiment including 17 groups of experiments was designed.

[0078] Table 2 Factor levels of response surface methodology

[0079]

[0080] Capacitor simulation models with different structural sizes R1, R2, and R3 are established for research, the Maxwell capacitance value is output, and the capacitance sensitivity and maximum penetration depth are calculated. The results are shown in the table below.

[0081] Table 3 Experimental design and results determination

[0082]

[0083] The response surface methodology was used to analyze the 17 data sets.

[0084] The analysis found that the P value of the capacitance sensitivity regression prediction model was less than 0.0001, indicating that the capacitance sensitivity regression model reached a very significant level. At the same time, the determination coefficient of the model, R2 = 0.9995, was close to 1, indicating that 99.95% of the experimental data could be explained by the model. The correlation coefficient further proved that the fitting degree of the model was reliable and that the capacitance sensitivity value could be effectively predicted. The signal-to-noise ratio of the model, Adeq Precision = 1471.22, indicated that the simulation test results of the model were accurate and reliable.

[0085] Further analysis found that the maximum penetration depth regression prediction model P < 0.0001, indicating that the maximum penetration depth regression model reached a very significant level, and the model's determination coefficient R2 = 0.9985 is close to 1, indicating that 99.85% of the experimental data can be explained by the model. The correlation coefficient further proves that the model's fitting degree is reliable and can effectively predict the capacitance sensitivity value, and the model's signal-to-noise ratio Adeq Precision = 521.53, indicating that the model simulation test results are accurate and reliable.

[0086] The response regression prediction model established in this way is:

[0087] Capacitor sensitivity = 0.5767 + 0.0929 * R1 - 0.0574 * R2 - 0.0022 * R3 - 0.0191 * R1R2 - 0.0004 * R1R3 - 0.0002 * R2R3 + 0.0118 * R1 2 +0.0078*R2 2 +0.0007*R3 2

[0088] Maximum penetration depth = 79.95-1.08*R1+1.52*R2+1.13*R3+0.1800*R1R2-0.0950*R1R3+0.0875*R2R3-0.1613*R1 2 -0.1588*R2 2 -0.0537*R3 2

[0089] The distribution diagram of the actual and predicted values ​​of output capacitance sensitivity and maximum penetration depth is shown in Fig.10 and Fig.11, the structural parameters of the sensor with the best performance are predicted to be R1=80.000mm, R2=107.534mm, and R3=150.000mm.

[0090] The embodiment of the present invention selects PAC-13 asphalt paved road surface for road thickness measurement, determines the optimal size of the annular coplanar capacitive sensor electrode plate as described above, establishes a detection device based on the electrode plate, and then uses the detection device to perform thickness detection.

[0091] The assembled annular coplanar capacitive sensor structure is shown in Fig.12 , including a circular excitation electrode plate 1.1, an annular receiving electrode plate 1.2, a substrate 1.5 to which the electrode plate is attached, an electrode plate shielding layer 1.6 arranged at the bottom of the substrate, and a substrate protection layer 1.7 outside the shielding layer.

[0092] A method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, wherein a detection device performs detection, and the detection comprises the following steps:

[0093] This embodiment selects a PAC-13 asphalt pavement to be tested, and forms PAC13 asphalt surface rutting plates with thicknesses of 2 cm, 3 cm, 4 cm, 5 cm, 6 cm, 7 cm, and 8 cm.

[0094] The PAC-13 grading curve is shown in the table below, and the optimal oil-stone ratio is 4.7%.

[0095]

[0096] The optimized annular coplanar capacitance sensor was used to measure and obtain the output capacitance of different thicknesses of the surface layers under the PAC-13 asphalt pavement.

[0097] The output capacitance value is processed to fit the curve of output capacitance and asphalt surface thickness under the target asphalt pavement, see Fig.13 , the relationship after fitting is shown in the following formula:

[0098]

[0099] Where C is the capacitance value measured by the sensor, and d is the thickness of the asphalt surface layer.

[0100] For example, select PAC-13 graded asphalt pavement, use an annular coplanar capacitance sensor to measure the capacitance, and obtain the capacitance data of 69pF. Substitute the data into the relationship curve to obtain the asphalt pavement surface layer thickness d as 4.2609cm.

[0101] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for optimizing the size of an electrode plate of a concentric coplanar capacitive sensor, characterized in that: The specific optimization steps are as follows: Using simulation software, establish simulation models of annular coplanar capacitive sensors and asphalt pavement surface layers with different structural parameters; Under the annular coplanar capacitive sensors with different structural parameters, the thickness of the asphalt pavement surface layer is changed and the capacitance value is output; The maximum penetration depth and capacitance sensitivity of the annular coplanar capacitance sensor were selected as performance optimization indicators, and the electrode plate structure size was selected as the influencing factor for single factor analysis. The structural parameter range of the annular coplanar capacitive sensor after single factor analysis was selected, and a response surface design experiment was carried out. Variance and response surface analysis were performed based on the experimental results to output the size of the annular coplanar capacitive sensor with optimal performance.

2. The method for optimizing the size of the electrode plates of the concentric and coplanar capacitive sensor according to claim 1, characterized in that: The maximum penetration depth capacitance value calculation formula is: C d =0.97×(C max -C0)+C0 In the formula, C d is the output capacitance value of the sensor when the maximum penetration depth is d, C0 is the capacitance value output by the sensor in the air, C max It is the maximum capacitance value output by the sensor as the thickness of the asphalt surface layer increases.

3. The method for optimizing the size of the electrode plates of the concentric and coplanar capacitive sensor according to claim 1, characterized in that: The capacitance sensitivity is calculated according to the following formula: δ=ΔC / Δd In the formula, δ is the sensitivity, △C is the change in capacitance, and △d is the thickness of the asphalt surface layer.

4. The method for optimizing the size of the electrode plates of the concentric and coplanar capacitive sensor according to claim 1, characterized in that: The structural parameters include: R1 is the radius of the excitation electrode, R2 is the inner radius of the receiving electrode, and R3 is the outer radius of the receiving electrode; The relationship between structural parameters and maximum penetrable thickness and sensitivity is: The capacitance sensitivity increases gradually with the increase of the radius of the excitation electrode, the capacitance value is positively correlated with the sensitivity, and the maximum penetration depth decreases with the increase of the radius of the excitation electrode; The capacitance sensitivity decreases gradually with the increase of the inner radius of the receiving electrode, and the maximum penetration depth increases with the increase of the inner radius of the receiving electrode; With the change of the outer radius of the receiving electrode, the change of the capacitance value and the sensitivity is not obvious, and the maximum penetrable penetration depth increases with the increase of the outer radius of the receiving electrode.

5. An electrode plate of a concentric and coplanar capacitive sensor, characterized in that: The size optimization method described in claim 1 is used for optimization.

6. The electrode plate of the concentric and coplanar capacitive sensor according to claim 2, characterized in that: The electrode plates are respectively a circular electrode plate and an annular electrode plate. The circular electrode plate is used as an excitation electrode, and the annular electrode plate is used as a receiving electrode.

7. A device for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, characterized in that: It includes the electrode plate as described in claim 3; and also includes: a substrate for the electrode plate to be attached, an electrode plate shielding layer arranged at the bottom of the substrate, and a substrate protection layer outside the shielding layer.

8. A method for detecting the thickness of an asphalt pavement surface layer based on coplanar capacitance, characterized in that: The detection device described in claim 4 is used for detection, and the specific steps are as follows: Select the target asphalt pavement to be tested and form asphalt pavements of different thicknesses; The output capacitance of the asphalt pavement surface layers of different thicknesses is obtained by measuring with a thickness detection device; The output capacitance data is processed to fit the relationship curve between the output capacitance and the asphalt surface thickness under the target asphalt pavement; For the target asphalt pavement to be tested, the capacitance is measured using a thickness detection device, and the thickness of the surface layer of the asphalt pavement to be tested is determined based on the relationship curve between the obtained capacitance value and the fitting.

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