Estimation method of asphalt pavement compaction holographic equivalent temperature and electronic equipment

Abstract

The invention relates to an asphalt pavement compaction holographic equivalent temperature estimation method and electronic equipment, and the method comprises the following steps: in the engineering implementation stage of asphalt pavement construction, actually measuring the initial temperature of the upper layer of the pavement during water sprinkling, and calculating the initial temperature of the lower layer of the pavement according to the initial temperature; in the engineering implementation stage of asphalt pavement construction, the environment temperature during initial pressure, the watering temperature amplitude and the balance temperature when the temperature change of the upper layer and the lower layer of an asphalt pavement is stable are actually measured; the actually measured and calculated temperatures are substituted into the temperature decay model under the watering condition obtained through fitting, and the temperature of the upper layer and the temperature of the lower layer of the asphalt pavement changing along with time are estimated; and calculating a holographic equivalent temperature considering the asphalt layer depth and the compaction time according to the temperature of the upper layer and the lower layer which change along with the time. Compared with the prior art, the holographic equivalent temperature pre-estimation method under the water sprinkling working condition has the advantages that the operation is simple and convenient, and the pre-estimation result has the advantages of being accurate, real-time and the like.

Description

Technical Field

[0001] The invention relates to the technical field of road engineering, and in particular to a method for estimating the holographic equivalent temperature of asphalt pavement compaction and electronic equipment. Background Art

[0002] Asphalt pavement needs to be watered during compaction to prevent the roller wheel from sticking to the asphalt mixture. Studies have shown that watering can cause the surface temperature of the asphalt pavement to drop sharply, but the temperature change pattern of the entire asphalt layer is different from that of the layer surface, and its temperature drop rate is slower than that of the layer surface. Currently, there are existing models that can describe the temperature change pattern, but they do not consider the impact of watering.

[0003] Due to the temperature sensitivity of asphalt mixture, the compaction temperature and distribution characteristics of asphalt pavement have a significant impact on the compaction quality. If the compaction temperature segregates, it will lead to uneven pavement compaction quality, which is manifested as uneven compaction. In areas with lower compaction temperatures, the compaction of the pavement is smaller and the texture depth is greater, which is prone to early damage. At present, some early damages of asphalt pavements, such as looseness, cracks, potholes, local severe rutting, local oil overflow, and uneven structural depth of newly paved asphalt pavements, are closely related to the uneven compaction caused by temperature segregation, and the uniformity of compaction is a key factor affecting the service life of asphalt pavements.

[0004] The uneven compaction caused by road surface segregation, looseness and other diseases will reduce the service life of asphalt pavement by 56% to 73%, and the cracks caused by it will also reduce the service life of the pavement by more than 50%. The previous research of the research team also showed that when the compaction is uneven (the pavement is divided into two sections, one section has a compaction of 91%, the other section has a compaction of 94%, and the average compaction of the pavement is 92.5%), compared with the case of uniform compaction (the overall compaction of the pavement is 92.5%), the service life of high-grade highways and other grades of highways is reduced by about 0.5 years. Therefore, clarifying the impact of watering on compaction temperature, compaction quality and service life is crucial to reducing or avoiding its early diseases and increasing the service life of asphalt pavements.

[0005] The prior art has the following defects:

[0006] 1. Lack of method to estimate initial temperature of asphalt pavement at different layer depths

[0007] At present, some commonly used methods for measuring pavement temperature, such as infrared thermometers and infrared cameras, can only measure the initial temperature of the surface, but cannot obtain the temperature at different depths. Although thermocouples and optical fiber sensing methods can measure the temperature at different depths, there are still some shortcomings. First, the temperature is sensitive to time changes, and there is an interval between detection times. The temperature at the end of the detection is no longer the real-time temperature, and the result lacks timeliness; second, in the actual construction process, the length of a single asphalt paving is usually measured in kilometers. If you want to obtain the temperature field of different layers within the paving length, you need a lot of temperature data support, and the current detection method cannot cover the entire plane.

[0008] 2. The effect of watering on compaction temperature decay is not considered

[0009] The roller needs to sprinkle water during operation. After a period of time, the surface temperature of the asphalt layer is significantly lower than the surrounding asphalt pavement. After the water evaporates, the temperature will gradually rise and approach the temperature of the surrounding asphalt pavement. If the layer surface temperature data is collected after the water sprinkling process, there will be a large error between the layer surface temperature measurement value and the actual temperature of the asphalt pavement as a whole.

[0010] 3. Lack of a temperature model based on space-time (holographic equivalent)

[0011] There are large differences in the temperature of asphalt pavement at different depths and at different times. The surface of the layer is in direct contact with the external environment, and watering is required during the compaction process, so the temperature is relatively low; while the other layers do not need to be watered, and there are differences in temperature, and the temperature will decay over time. Therefore, using the temperature of a single layer or a certain moment as a technical indicator lacks representativeness.

[0012] 4. Lack of consideration of the evaluation of the effect of compaction temperature on compaction quality supervision under watering conditions

[0013] The current temperature prediction model has problems such as unclear parameter meaning, limited applicability, and failure to consider the impact of watering. Therefore, it fails to effectively supervise the compaction quality, and there is no way to evaluate its supervision effect. First, the model cannot effectively guide construction practice and cannot properly supervise the compaction quality; second, it cannot provide feedback through evaluation to form a construction benchmark.

[0014] How to predict the holographic equivalent temperature of asphalt pavement compaction under watering conditions has become a technical problem that needs to be solved. Summary of the invention

[0015] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a method and electronic equipment for estimating the holographic equivalent temperature of asphalt pavement compaction.

[0016] The purpose of the present invention can be achieved by the following technical solutions:

[0017] According to one aspect of the present invention, a method for estimating the holographic equivalent temperature of asphalt pavement compaction is provided, the method comprising the following steps:

[0018] Step S1, during the engineering implementation phase of asphalt pavement construction, the initial temperature T of the upper layer of the pavement when water is sprinkled is measured. t0 , and according to the initial temperature T t0 Calculate the initial temperature T of the lower layer of the pavement b0 ;

[0019] Step S2, during the engineering implementation phase of asphalt pavement construction, the ambient temperature H at the time of initial pressure is measured. t0 , Sprinkler temperature amplitude ΔT C , the equilibrium temperature H when the temperature changes of the upper and lower layers of the asphalt pavement are stable t1 , H b1 ;

[0020] Step S3, substituting the temperatures measured and calculated in step S1 and step S2 into the temperature decay model under the watering condition obtained by fitting, and estimating the temperature of the upper layer and the lower layer of the asphalt pavement that changes with time after the initial pressure watering;

[0021] Step S4, based on the upper and lower layer temperatures that change with time after initial compaction and watering, calculate the holographic equivalent temperature that takes into account the asphalt layer depth and compaction time.

[0022] Preferably, the initial temperature of the lower layer of the asphalt pavement is calculated by weighting the temperature in the layer and the temperature at the bottom of the layer to obtain the initial temperature of the lower layer of the asphalt pavement, wherein the position in the layer is the position of the total thickness of the asphalt layer / 2, and the position at the bottom of the layer is the position of the total thickness of the asphalt layer;

[0023] The initial temperature calculation method of the lower layer of the asphalt pavement is:

[0024]

[0025] Where, T b0 is the initial temperature of the lower layer of the asphalt pavement; Zα α is the quantile of the temperature of the upper and lower layers of the asphalt pavement at the significance level α; T2(t0) and T3(t0) represent the temperature in the layer and the temperature at the bottom of the layer corresponding to the initial paving time t0, respectively.

[0026] More preferably, the calculation process of the temperature in the layer includes:

[0027] Calculate the temperature T1(x±(h / 2),y±(h / 2)) at a point h / 2 from the layer surface, specifically:

[0028]

[0029] Where h is the total thickness of the asphalt layer, T1(x,y) is the temperature of any point (x,y) in the temperature field of the layer surface plane;

[0030] Assuming that the natural logarithm of the temperature of points at the same depth or plane direction from the plane point conforms to the normal distribution, the probability density expression of the logarithm of the temperature in the layer corresponding to the center point is;

[0031]

[0032] Among them, T2(x,y) is the temperature in the layer; μ2(x,y) is the mean of the probability density function of the logarithmic value of the temperature in the layer; σ2(x,y) is the standard deviation of the probability density function of the logarithmic value of the temperature in the layer.

[0033] More preferably, the bottom temperature calculation process includes:

[0034] Calculate the temperature T1(x±h,y±h) of the surface point of the layer at the distance layer surface point h, specifically:

[0035]

[0036] Where h is the total thickness of the asphalt layer, T1(x,y) is the temperature of any point (x,y) in the temperature field of the layer surface plane;

[0037] Assuming that the natural logarithm of the temperature of points at the same depth or plane direction from the plane point conforms to the normal distribution, the probability density expression of the logarithm of the bottom temperature corresponding to the center point is:

[0038]

[0039] Among them, T3(x,y) is the bottom temperature; μ3(x,y) is the mean of the probability density function of the logarithmic value of the bottom temperature; σ3(x,y) is the standard deviation of the probability density function of the logarithmic value of the bottom temperature.

[0040] Preferably, the temperature decay model under the watering condition includes a temperature decay model for the upper layer of the asphalt pavement and a temperature decay model for the lower layer of the asphalt pavement;

[0041] The fitting process of the temperature decay model under the watering condition is as follows: the initial temperature T of the upper layer of the asphalt pavement collected during the test phase of asphalt pavement construction is t0 , according to the initial temperature T t0 Calculate the initial temperature T of the lower layer of the pavement b0 , and the ambient temperature H when the initial pressure is measured t0 , Sprinkler temperature amplitude ΔT C , the temperature T of the upper and lower layers of the asphalt pavement changing with time t t , T bThe equilibrium temperature H when the temperature changes steadily t1 , H b1 , substituted into the corresponding asphalt pavement upper layer watering temperature decay model and lower layer temperature decay model, fitted the temperature change law over time, and obtained the fitting parameters k in the asphalt pavement upper layer watering temperature decay model respectively. t1 , k t2 , and the fitting parameter k in the lower temperature decay model b1 , k b2 .

[0042] More preferably, the watering temperature decay model of the upper layer of the asphalt pavement is specifically:

[0043]

[0044] Where, T t is the temperature of the upper layer of the asphalt pavement changing with time t; T t0 ΔT is the initial temperature of the upper layer of the asphalt pavement when water is initially applied; C H is the variation range of watering temperature; t0 is the ambient temperature during initial compaction; H t1 k is the temperature when the ambient temperature and the pavement temperature tend to be balanced and stable; t1 , k t2 are the fitting parameters in the model.

[0045] More preferably, the temperature decay model of the lower layer of the asphalt pavement is specifically:

[0046]

[0047] Where, T b is the temperature of the lower layer of the asphalt pavement changing with time t; T b0 is the initial temperature of the lower layer of the asphalt pavement; H b1 k is the temperature when the lower layer temperature and the pavement temperature tend to be balanced and stable; b1 , k b2 are the fitting parameters in the model.

[0048] Preferably, the equivalent temperature calculation considering the depth of the asphalt layer is specifically as follows:

[0049]

[0050] Where, T s is the equivalent temperature of the asphalt pavement; h1 is the thickness of the upper layer of the asphalt pavement; h2 is the thickness of the lower layer of the asphalt pavement; h is the total thickness of the asphalt pavement, h = h1 + h2; T t and T b They are the temperatures of the upper and lower layers of the pavement changing with time.

[0051] Preferably, the holographic equivalent temperature calculation considering the compaction time is specifically as follows:

[0052]

[0053] Where, T is the holographic equivalent temperature of the asphalt pavement; t1, t2, t3, t4 and t5 are different compaction times; t is the total compaction time, t = t1 + t2 + t3 + t4 + t5; T s1 , T s2 , T s3 , T s4 and T s5 The equivalent temperature of asphalt pavement corresponding to different compaction times.

[0054] According to another aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the method described above is implemented when the processor executes the program.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1) The present invention calculates the initial temperature of the lower layer through the initial temperature of the upper layer of the asphalt pavement when watering, substitutes the various temperatures measured in the project implementation stage and the calculated temperatures into the fitted temperature decay model under the watering condition, estimates the upper and lower layer temperatures that change with time after the initial pressure and watering of the asphalt pavement, and then calculates the holographic equivalent temperature of the asphalt pavement under the watering condition. Because the holographic equivalent temperature takes into account the watering condition, the depth of the asphalt layer and the compaction time, it represents the temperature of the entire asphalt layer and the entire compaction process. Compared with the existing estimation method, the accuracy of the estimation result is improved.

[0057] 2) The method for estimating the initial temperature of different layer depths of asphalt pavement proposed in the present invention can quickly obtain a large sample of initial temperature data of the middle, surface and lower layers of the pavement in the construction area by simply measuring the upper layer temperature of the pavement through calculation, which helps to solve the difficulty that the existing pavement detection method requires a large amount of temperature data support, and the estimation result is real-time.

[0058] 3) The watering temperature decay model of the present invention is applied to the test section, and the model R 2 The mean value is 0.9940, which verifies that the model has a good fitting effect and can better characterize the decay of the compaction temperature of asphalt pavement under watering conditions, and can be used to estimate the holographic equivalent temperature.

[0059] 4) The correlation between the holographic equivalent temperature and the compaction degree estimated by the present invention is 0.833, and the two are significantly correlated. The temperature data can be used for holographic supervision of the compaction quality of asphalt pavement to improve the compaction quality.

[0060] 5) The holographic equivalent temperature estimation method of the present invention provides theoretical support for reducing watering. Reducing the amount of watering can save construction costs, reduce compaction temperature loss, and improve compaction. Compared with normal watering, the compaction degree of asphalt pavement during reduced watering is increased by an average of 2.21%, and the service life is extended by 3.71 years. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic flow chart of the method for estimating the holographic equivalent temperature of asphalt pavement compaction in the present invention;

[0062] Figure 2 It is a schematic diagram comparing the fitting results of the layer surface temperature at the test section pile number K0+110 of the original model and the present invention;

[0063] Figure 3 It is a schematic diagram comparing the fitting results of the layer surface temperature at the test section pile number K0+120 of the original model and the present invention;

[0064] Figure 4 It is a schematic diagram comparing the fitting results of the layer surface temperature at the pile number K0+130 of the test section of the original model and the present invention;

[0065] Figure 5 It is a schematic diagram comparing the fitting results of the layer surface temperature at the test section pile number K0+140 of the original model and the present invention;

[0066] Figure 6 It is a schematic diagram comparing the fitting results of the layer surface temperature at the test section pile number K0+160 of the original model and the present invention;

[0067] Figure 7 It is a schematic diagram comparing the fitting results of the layer surface temperature at the pile number K0+170 of the test section of the original model and the present invention;

[0068] Figure 8 It is a schematic diagram comparing the fitting results of the layer surface temperature at the test section pile number K0+200 of the original model and the present invention;

[0069] Fig. 9 Comparison of fitting results of layer surface temperature at pile number K0+230 of the test section between the original model and the present invention;

[0070] Fig.10 Comparison of fitting results of layer surface temperature at pile number K0+250 in the test section between the original model and the present invention;

[0071] Fig.11 Comparison of fitting results of layer surface temperature at pile number K0+280 of the test section between the original model and the present invention;

[0072] Fig.12 Comparison of the fitting results of the layer surface temperature at the test section pile number K0+320 between the original model and the present invention;

[0073] Fig.13 Comparison of fitting results of layer surface temperature at pile number K0+330 of the test section between the original model and the present invention;

[0074] Fig.14 Comparison of fitting results of layer surface temperature at pile number K0+360 in the test section between the original model and the present invention;

[0075] Fig.15 Comparison of fitting results of layer surface temperature at pile number K0+380 of the test section between the original model and the present invention;

[0076] Fig.16 Comparison of fitting results of layer surface temperature at pile number K0+390 of the test section between the original model and the present invention;

[0077] Fig.17 The comparison results of the watering amount between the traditional watering and the improved spraying in the present invention;

[0078] Fig.18 It is a schematic diagram of the relationship between temperature and compaction degree under different watering conditions in the present invention;

[0079] Fig.19 It is a schematic diagram of the fitting results of the relationship between compaction degree and service life in the present invention. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0081] Example 1

[0082] This embodiment relates to a method for estimating the holographic equivalent temperature of asphalt pavement compaction. Figure 1 ,include:

[0083] In the first stage, a method for estimating the initial temperature of different layer depths of asphalt pavement is given;

[0084] In the second stage, a temperature decay model of asphalt pavement under watering conditions was proposed, based on which the temperature of the upper and lower layers of the asphalt pavement changing with time during the project implementation phase was estimated;

[0085] In the third stage, a holographic equivalent temperature model based on water sprinkling is proposed, based on which the holographic equivalent temperature of the asphalt pavement is estimated during the project implementation phase.

[0086] In the first stage, because the heat conduction efficiency at the bottom of the pavement layer is higher than the heat convection at the surface, the asphalt pavement is divided into an upper layer and a lower layer. The thickness range from the surface to the top of the middle layer is defined as the upper layer of the asphalt pavement, and the thickness range from the top of the middle layer to the bottom of the layer is defined as the lower layer of the asphalt pavement.

[0087] Step 1: During the test phase of asphalt pavement construction, the initial temperature of the layer surface is first obtained by capturing it with an infrared imager, which is used as the initial temperature T when water is sprinkled on the upper layer of the pavement. t0 According to the initial temperature T when the upper layer is sprinkled t0 Calculate the initial temperature of the layer and the bottom of the layer, and then calculate the initial temperature T of the lower layer of the pavement b0 .

[0088] Estimation of initial temperature in and at the bottom of asphalt pavement

[0089] The general idea is: the total thickness of the asphalt layer is h, the position at the thickness of h / 2 is selected to represent the position in the layer, and the position at the thickness of h represents the position at the bottom of the layer. It is assumed here that the temperature distribution of points at the same depth or plane direction from the plane point obeys the same statistical law, and the natural logarithm of the temperature conforms to the normal distribution. Therefore, the solution of the three-dimensional temperature field in space can be converted into the solution of the plane temperature field, that is, by measuring the temperature of a certain point on the layer surface, on the same plane, with this point as the center of the circle, the temperature of the points on the circle with a radius of h / 2 and h is calculated respectively, as the temperature in the layer and at the bottom of the layer corresponding to the center point of the circle. A large number of measurement points are selected, and the representative temperature of the layer and the bottom of the layer can be obtained by calculation.

[0090] The specific steps are:

[0091] ①T1(x,y) is the temperature of any point (x,y) in the plane temperature field of the layer surface. The coordinates of the remaining points in the plane temperature field can be expressed by the positional relationship with (x,y), and the decay between the temperature of the point and the temperature of the point (x,y) is proportional to the distance between the two points. Therefore, the temperature of each point in the plane temperature field can be expressed by the temperature relationship of the point (x,y) through the distance formula between the two points. The temperature of the layer surface point at 0.5h and h away from the point (x,y) can be expressed by Formula 1 and Formula 2 respectively.

[0092]

[0093]

[0094] Where T1(x±(h / 2),y±(h / 2)) and T1(x±h,y±h) are the temperatures at 0.5h and h from the layer surface point T1(x,y) respectively.

[0095] ② After finding the temperature of each point on the circle with radius h / 2 and h, based on the basic assumption, the temperature in the layer and the bottom of the layer corresponding to the center point are solved by the expression of normal distribution. The probability density expressions of the logarithmic values ​​of the temperature in the layer and the bottom of the layer are shown in Formula 3 and Formula 4 respectively.

[0096]

[0097]

[0098] Where T2(x,y) and T3(x,y) are the temperature in the layer and the temperature at the bottom of the layer respectively; μ2(x,y) and μ3(x,y) are the means of the probability density functions of the logarithmic values ​​of the temperature in the layer and the temperature at the bottom of the layer respectively; σ2(x,y) and σ3(x,y) are the standard deviations of the probability density functions of the logarithmic values ​​of the temperature in the layer and the temperature at the bottom of the layer respectively.

[0099] Estimation of initial temperature of lower layer of asphalt pavement

[0100] The calculated layer middle and layer bottom temperatures are weighted as the initial representative temperature of the lower layer of the asphalt pavement. The calculation method of the initial temperature of the lower layer is shown in Formula 5.

[0101]

[0102] Where, T b0 is the initial representative temperature of the lower layer of the asphalt pavement, unit: °C; Zα α is the quantile of the upper and lower layer temperatures at the significance level α; T2(t0) and T3(t0) represent the temperature in the layer and the temperature at the bottom of the layer corresponding to time t0, respectively, where t0 is the initial paving time, and t0=0 initially.

[0103] Step 2: During the test phase of asphalt pavement construction, measure the ambient temperature H at the initial pressure. t0 , Sprinkler temperature amplitude ΔT C , the temperature T of the upper and lower layers of the asphalt pavement changing with time t t , T b The equilibrium temperature H when the temperature changes steadily t1 , H b1 .

[0104] In the second stage, the temperature decay model of the upper layer of asphalt pavement considering water sprinkling

[0105] Step 3: Substitute the initial temperature in step 1 and the measured temperatures in step 2 into the corresponding temperature decay model of the upper and lower layers of the asphalt pavement, fit the temperature variation over time, and obtain the fitting parameters k in the temperature decay model of the upper layer of the asphalt pavement. t1 , k t2 , and the fitting parameter k in the lower temperature decay modelb1 , k b2 .

[0106] Temperature decay model of the upper layer of asphalt pavement by watering: During the construction of asphalt pavement, the decay of its compaction temperature is affected by environmental factors, including heat conduction between the upper and lower layers of the pavement, atmospheric heat convection, and solar heat radiation. At the same time, the upper layer of the pavement needs to be watered during the compaction process to prevent the roller from sticking to the asphalt mixture. After watering, the water evaporates and absorbs heat and then gradually heats up, which will also affect the compaction temperature of the asphalt pavement, and the temperature change caused by watering cannot be ignored. Therefore, taking Newton's cooling law as the theoretical basis for model establishment and considering the influence of watering conditions, the temperature decay model of the upper layer of asphalt pavement by watering is shown in Formula 6.

[0107]

[0108] Where: T t0 is the initial temperature of the upper layer of the asphalt pavement when water is initially applied, obtained through measured data, ℃; ΔT C is the variation range of watering temperature, obtained through measured data, ℃; H t0 is the ambient temperature at the initial compaction (t = 0), obtained through measured data, °C; H t1 is the temperature when the ambient temperature and the pavement temperature tend to be balanced and stable, obtained through measured data, ℃; k t1 , k t2 are the fitting parameters in the model.

[0109] Asphalt pavement lower layer temperature decay model: Since there is heat conduction between the upper and lower layers of the asphalt pavement, but the lower layer does not consider the watering situation, the lower layer temperature decay model adopts the upper layer model without considering the watering situation, such as

[0110] As shown in formula 7.

[0111]

[0112] Where: T b0 is the initial temperature of the lower layer of the asphalt pavement when initially pressed and watered, obtained by calculation, ℃; H b1 is the temperature when the lower layer temperature and the pavement temperature tend to be balanced and stable, obtained through measured data, ℃; k b1 , k b2 are the fitting parameters in the model.

[0113] Step 4: During the engineering implementation phase of asphalt pavement construction, measure the initial temperature T of the upper layer of the pavement when water is sprinkled. t0 , and calculate the initial temperature T of the lower layer of the pavement b0 ; The ambient temperature H when the initial pressure is measured t0 , Sprinkler temperature amplitude ΔTC , the equilibrium temperature H when the temperature changes of the upper and lower layers of the asphalt pavement are stable t1 , H b1 .

[0114] Step 5: Substitute the measured and calculated temperatures obtained during the project implementation phase (i.e., the results of step 4) into the fitted temperature decay model to estimate the temperature T of the upper and lower layers of the asphalt pavement over time during the project implementation phase. t , T b .

[0115] In the third stage, the estimation of the holographic equivalent temperature of asphalt pavement compaction under watering conditions is as follows:

[0116] Step 6: Based on the results of step 5, calculate the equivalent temperature considering the depth of the asphalt layer

[0117] The equivalent temperature of the asphalt pavement is obtained by weighting and summing the decay temperatures of the upper and lower layers of the asphalt pavement according to the ratio of their layer thickness to the total layer thickness. The calculation method is shown in Formula 8.

[0118]

[0119] Where: T s is the equivalent temperature of the asphalt pavement, °C; h1 is the thickness of the upper layer of the asphalt pavement, cm; h2 is the thickness of the lower layer of the asphalt pavement, cm; h is the total thickness of the asphalt pavement, h = h1 + h2, cm, T b is the temperature of the lower layer of the asphalt pavement after initial pressure and watering, which changes with time t. t It is the temperature change over time of the upper layer of asphalt pavement after initial pressure and watering.

[0120] Step 7: Calculate the holographic equivalent temperature considering the compaction time

[0121] The equivalent temperature of the asphalt pavement obtained in step 6 is weighted and summed according to the proportion of the corresponding compaction time to the total compaction time, to obtain the holographic equivalent temperature of the asphalt pavement. The calculation method is shown in formula 9.

[0122]

[0123] Where: T is the holographic equivalent temperature of the asphalt pavement, °C; t1, t2, t3, t4, t5 are different compaction times, min; t is the total compaction time, t = t1 + t2 + t3 + t4 + t5, min; T s1 , T s2 , T s3 , T s4 , T s5 They are the equivalent temperatures of asphalt pavement corresponding to different compaction times, ℃.

[0124] Example 2

[0125] This embodiment relates to a method for estimating the holographic equivalent temperature of asphalt pavement compaction under watering conditions. An arbitrary point is selected on the plane temperature field. According to the temperature estimation method in the asphalt pavement layer and at the bottom of the layer, the temperatures of eight points at a distance of 0.5h and h from the point are calculated, a total of 16 point temperatures, as the temperatures in the layer and at the bottom of the layer corresponding to the selected point. A total of 48,000 temperature points are collected on the layer surface, and 30 points are selected for calibration verification. The original data of the temperature in the layer and at the bottom of the layer, the calibration results, and the test results are shown in Tables 1 and 2, respectively.

[0126] Table 1

[0127] serial number 1 2 3 4 5 6 7 8 W <![CDATA[μ2]]> <![CDATA[σ2]]> 1 160.0 166.0 165.0 166.0 165.1 165.7 164.6 164.6 0.875 5.1074 0.0036 2 166.0 166.0 165.0 166.0 166.7 165.6 165.6 165.0 0.917 5.1104 0.0035 3 157.0 157.0 155.0 159.0 157.7 156.6 156.6 157.1 0.932 5.0562 0.0072 4 157.0 159.0 159.0 157.0 155.3 157.0 158.1 157.6 0.917 5.0594 0.0078 5 152.0 148.0 154.0 150.0 151.0 150.4 149.3 152.1 0.990 5.0163 0.0124 6 155.0 158.0 153.0 153.0 154.3 156.0 155.4 153.1 0.903 5.0416 0.0113 7 148.0 154.0 145.0 152.0 148.7 150.4 149.3 149.8 0.982 5.0082 0.0180 8 150.0 150.0 151.0 148.0 150.3 150.8 149.7 149.1 0.930 5.0097 0.0064 9 144.0 142.0 144.0 144.0 143.0 143.0 143.0 143.0 0.827 4.9646 0.0049 10 141.0 145.0 145.0 147.0 144.1 142.4 144.1 145.8 0.960 4.9719 0.0131 11 139.0 143.0 141.0 143.0 141.1 141.1 140.6 141.7 0.921 4.9510 0.0092 12 138.0 142.0 139.0 143.0 140.8 138.0 140.8 140.8 0.912 4.9438 0.0130 13 132.0 135.0 132.0 138.0 134.5 133.4 134.0 134.0 0.896 4.8985 0.0142 14 133.0 131.0 134.0 133.0 132.0 130.9 133.1 133.1 0.879 4.8867 0.0084 15 128.0 132.0 126.0 128.0 128.1 131.0 129.3 128.1 0.914 4.8583 0.0147 16 128.0 131.0 129.0 128.0 126.4 128.7 129.3 127.6 0.969 4.8558 0.0105 17 123.0 130.0 124.0 127.0 124.3 126.0 126.0 126.0 0.944 4.8182 0.0076 18 124.0 123.0 125.0 122.0 124.0 124.6 124.0 123.4 0.891 4.8176 0.0112 19 118.0 118.0 116.0 122.0 118.4 117.8 117.3 118.4 0.822 4.7726 0.0143 20 119.0 122.0 120.0 121.0 120.1 121.3 120.1 119.6 0.965 4.7907 0.0081 21 118.0 121.0 112.0 118.0 116.1 119.5 119.0 115.6 0.940 4.7653 0.0240 22 114.0 128.0 111.0 113.0 112.1 121.2 119.5 110.4 0.873 4.7537 0.0521 23 103.0 100.0 106.0 102.0 105.4 103.7 104.9 105.4 0.911 4.6424 0.0200 24 103.0 104.0 105.0 102.0 107.0 104.7 106.4 105.9 0.971 4.6515 0.0163 25 102.0 101.0 106.0 102.0 105.0 101.6 103.3 105.6 0.887 4.6376 0.0189 26 106.0 105.0 104.0 108.0 107.3 106.1 105.0 106.1 0.963 4.6628 0.0121 27 99.0 107.0 97.0 102.0 101.8 103.5 103.0 99.6 0.978 4.6207 0.0304 28 104.0 104.0 101.0 100.0 98.4 99.6 100.7 100.7 0.883 4.6154 0.0196 29 99.0 96.0 97.0 97.0 98.1 96.4 95.3 97.0 0.957 4.5745 0.0120 30 97.0 98.0 92.0 96.0 96.8 96.8 93.4 93.4 0.882 4.5583 0.0229

[0128] Table 2

[0129] serial number 1 2 3 4 5 6 7 8 W <![CDATA[μ3]]> <![CDATA[σ3]]> 1 165.0 166.0 165.0 167.0 164.3 163.9 164.3 164.1 0.877 5.1056 0.0065 2 167.0 166.0 166.0 165.0 165.3 164.9 165.1 165.0 0.843 5.1092 0.0045 3 158.0 158.0 153.0 159.0 156.4 155.9 156.4 156.3 0.922 5.0165 0.0075 4 157.0 156.0 157.0 159.0 156.9 157.1 155.6 157.1 0.870 5.0560 0.0064 5 149.0 151.0 153.0 150.0 151.3 150.9 151.1 150.9 0.922 5.0165 0.0075 6 154.0 154.0 152.0 157.0 152.7 151.7 152.6 152.4 0.828 5.0324 0.0111 7 153.0 151.0 148.0 151.0 147.6 146.3 147.8 147.1 0.887 5.0037 0.0158 8 150.0 150.0 150.0 147.0 148.1 147.7 148.3 147.7 0.843 5.0013 0.0081 9 142.0 143.0 144.0 143.0 143.3 142.9 143.0 142.7 0.915 4.9627 0.0039 10 143.0 147.0 144.0 146.0 143.0 142.4 143.1 143.4 0.824 4.9697 0.0112 11 138.0 141.0 140.0 143.0 140.1 140.0 139.7 140.4 0.909 4.9436 0.0099 12 138.0 139.0 139.0 140.0 138.7 137.6 138.3 138.4 0.969 4.9318 0.0053 13 133.0 139.0 135.0 137.0 130.6 128.7 131.0 131.3 0.945 4.8915 0.0263 14 134.0 131.0 136.0 137.0 132.6 131.9 132.3 132.6 0.893 4.8933 0.0157 15 129.0 132.0 126.0 129.0 127.7 126.4 128.1 127.4 0.920 4.8536 0.0145 16 125.0 131.0 130.0 133.0 127.3 126.7 126.7 128.3 0.955 4.8557 0.0205 17 124.0 132.0 124.0 129.0 122.7 120.2 123.4 123.0 0.867 4.8262 0.0302 18 124.0 123.0 126.0 121.0 124.1 123.9 123.9 123.6 0.891 4.8176 0.0112 19 121.0 118.0 115.0 117.0 116.3 114.7 116.0 115.3 0.867 4.7591 0.0175 20 118.0 122.0 121.0 122.0 119.1 119.3 119.7 119.4 0.907 4.7880 0.0120 21 117.0 122.0 112.0 118.0 115.4 114.4 116.3 115.1 0.956 4.7558 0.0250 22 117.0 119.0 111.0 120.0 112.8 110.3 112.6 112.4 0.876 4.7391 0.0324 23 108.0 103.0 105.0 104.0 106.0 106.3 106.4 105.6 0.976 4.6589 0.0147 24 106.0 104.0 105.0 104.0 107.1 107.3 107.4 106.6 0.867 4.6627 0.0135 25 108.0 101.0 105.0 104.0 105.0 105.3 105.8 104.7 0.902 4.6525 0.0187 26 108.0 103.0 104.0 107.0 105.6 105.4 105.0 105.4 0.964 4.6579 0.0149 27 102.0 108.0 95.0 114.0 101.5 98.2 100.4 100.8 0.919 4.6284 0.0567 28 110.0 98.0 102.0 104.0 99.7 98.9 100.0 99.3 0.822 4.6192 0.0379 29 99.0 97.0 95.0 98.0 97.7 97.4 97.3 96.9 0.926 4.5776 0.0118 30 98.0 96.0 91.0 94.0 94.3 94.1 94.8 93.4 0.953 4.5480 0.0213

[0130] From the results in Table 1 and Table 2, it can be seen that when the significance level is 0.05 and the sample size is 8, the W test statistic of the logarithmic values ​​of the temperature in the layer and at the bottom of the layer is greater than 0.818, indicating that the logarithmic value of the temperature conforms to the normal distribution, proving the validity of the basic assumption. This method can be used to estimate the initial temperature of different layer depths of asphalt pavement, which not only realizes the acquisition of a large sample of temperature in the construction area, but also has real-time estimation results. Among them, μ2 and μ3 are the means of the probability density functions of the logarithmic values ​​of the temperature in the layer and the bottom of the layer respectively; σ2 and σ3 are the standard deviations of the probability density functions of the logarithmic values ​​of the temperature in the layer and the bottom of the layer respectively.

[0131] Example 3

[0132] This embodiment also relates to a method for estimating the holographic equivalent temperature of asphalt pavement compaction under watering conditions. A test section with a length of 749m, a width of 7m, and a watering amount of 667kg is selected. The initial paving temperature of the asphalt pavement layer is measured at the test section pile number K0+110 as the starting point. The temperature change value T0, the ambient temperature H0, and the watering temperature change amplitude ΔT C And the collection of equilibrium temperature H1 data, the results are shown in Table 3.

[0133] Table 3

[0134]

[0135] The temperature decay model parameters were fitted according to the data in Table 3. The results are shown in Table 4. The curve fitting results of each pile number in the test section are shown in Figure 2 to Figure 16The fitted temperature decay model is referred to the previous holographic equivalent temperature calculation method to obtain the result of the holographic equivalent temperature T of asphalt pavement compaction under the sprinkler condition, as shown in Table 4, where k t1 and k t2 are the fitting parameters in the temperature decay model of the upper layer of asphalt pavement.

[0136] Table 4

[0137]

[0138] Table 4

[0139]

[0140] From Table 4 and Figure 2 to Figure 16 It can be seen that the temperature calculated by the temperature decay model without considering watering is significantly different from the temperature measured after watering, indicating that the model without considering watering cannot well characterize the temperature decay of asphalt pavement compaction under watering conditions. Therefore, by introducing the temperature change amplitude ΔT C , the model without considering watering is improved. At the same time, the improved model R 2 The index range is 0.9880~0.9999, and the fitting effect is good, which can better characterize the decay of the compaction temperature of asphalt pavement under the condition of watering. Compared with the model without considering watering, the mean square error of the model after considering watering is reduced by 98.9% year-on-year;

[0141] Example 4

[0142] This embodiment also relates to a method for estimating the holographic equivalent temperature of asphalt pavement compaction under watering conditions. The temperature estimated by the method proposed in the present invention represents the temperature of the entire asphalt layer and the entire compaction process. The correlation between the layer surface temperature and the compaction degree is only 0.549, while the correlation between the holographic equivalent temperature and the compaction degree is 0.833, indicating that the two are significantly correlated. Temperature data can be used for holographic supervision of the compaction quality of asphalt pavements to improve the compaction quality. The improvement in compaction quality has an impact on the service life. Data from the Long-Term Pavement Performance (LTPP) project were selected to explore the impact between the compaction degree and service life of asphalt pavements.

[0143] Data screening follows the following principles: (1) The road grade is high and the structure is a flexible base asphalt pavement; (2) The difference between the compaction collection date and the initial construction date of the road is less than one year; (3) The time from the initial construction of the road to the start of recording of disease data is less than 5 years; (4) The pavement maintenance quality index (PQI, Pavement Maintenance Quality Index, ranging from 0 to 100) when the road was first built is above 95, and only minor repairs and maintenance are carried out during the data selection period. When the PQI is lower than 60, only the decay performance data within one life cycle is retained. Finally, only 8 sections of roads were screened. The compaction and service life of the selected roads were calculated based on the data information, and the results are shown in Table 5.

[0144] Table 5

[0145] Road Code Road Performance Index Compactness(K,%) Service life (SL, years) 4-0261 39.43 91.14 11.03 27-1003 58.69 95.77 13.92 27-1017 56.70 96.26 11.85 40-0114 62.42 96.26 19.08 81-A902 60.10 94.40 17.56 87-0901 54.42 95.53 12.58 87-0902 46.99 92.71 8.48 87-0903 49.25 93.15 9.48

[0146] The relationship between the compaction degree and service life of asphalt pavement was analyzed based on the results in Table 5. The compaction degree was used as the horizontal axis and the service life was used as the vertical axis. A linear model was used to draw a fitting curve. The results are shown in Fig.17 The fitting equation is: SL = 1.678K-146.017. The results show that the correlation coefficient between compaction and service life is 0.675, and there is a positive correlation. When the compaction degree increases by 1%, the service life of the asphalt pavement increases by 1.678 years.

[0147] Example 5

[0148] This embodiment also relates to a method for estimating the holographic equivalent temperature of asphalt pavement compaction under watering conditions.

[0149] The watering temperature decay prediction model proposed in the present invention can be used as a theoretical basis for reduced watering and compaction to obtain the minimum watering amount without sticking to the wheel, that is, the theoretical minimum spraying amount per square meter.

[0150] Through on-site data collection, a section of road 749m long and 7m wide has an approximate watering volume of 0.667 tons. It can be calculated that under normal watering conditions, the water consumption per square kilometer is 7.60 tons. The width of the steel wheel of the on-site roller is 2.1m and the diameter is 1.5m. The watering method has been improved from irrigation to spraying. The optimal atomizing nozzle can reduce the total flow rate to 4.6L / min, a year-on-year decrease of 26.0%; by using the control system to control the spray device, and at the same time cooperating with the surfactant with the best effect of reducing the surface energy of the liquid, the liquid coverage rate is increased by 22.0%. Finally, the weight of the droplets on the steel wheel is reduced to 54.2g / m 2 , the total water consumption was reduced from 0.667 tons to 0.473 tons, and the water consumption per square kilometer was reduced by 3.02 tons, that is, the theoretical minimum watering amount was 4.61 tons per square kilometer. The results are shown in Table 6 and Fig.18shown.

[0151] Table 6

[0152] Original sprinkler system Improved sprinkler system Reduction Water consumption (kg) 667 473 194 <![CDATA[Unit water consumption (t / km 2 )]]> 7.63 4.61 3.02

[0153] At the asphalt paving site, test points were selected and water sprinkling and water reduction measures were taken at the test points to determine the initial paving temperature of the layer surface. The density of the previously selected temperature measurement points was measured using a non-nuclear density meter, and the corresponding compaction degree was calculated. The results are shown in Table 7 and Fig.19 shown.

[0154] Table 7

[0155]

[0156] From Table 7 and Fig.19 It can be seen that watering has an impact on the compaction of asphalt pavement. At the same initial paving temperature, the temperature decay amplitude of the reduced watering area is smaller than that of the normal watering area, and the compaction is closely related to the compaction temperature, and the change law is similar. Therefore, the compaction of the reduced watering area is higher than that of the normal watering area, with an average increase of 2.21%. According to the quantification results of service life and compaction, the reduced watering can extend the service life by about 3.71 years. The results show that reducing the amount of watering is conducive to improving the compaction of asphalt pavement and extending the service life of asphalt pavement.

[0157] Example 6

[0158] The electronic device of the present invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0159] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0160] The processing unit performs the various methods and processes described above, such as methods S1 to S7. For example, in some embodiments, methods S1 to S7 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into the RAM and executed by the CPU, one or more steps of methods S1 to S7 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute methods S1 to S7 in any other appropriate manner (e.g., by means of firmware).

[0161] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0162] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0163] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0164] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for estimating the holographic equivalent temperature of asphalt pavement compaction, characterized in that: The method comprises the following steps: Step S1, during the engineering implementation phase of asphalt pavement construction, the initial temperature T of the upper layer of the pavement when water is sprinkled is measured. t0 , and according to the initial temperature T t0 Calculate the initial temperature T of the lower layer of the pavement b0 ; Step S2, during the engineering implementation phase of asphalt pavement construction, the ambient temperature H at the time of initial pressure is measured. t0 , Sprinkler temperature amplitude ΔT C , the equilibrium temperature H when the temperature changes of the upper and lower layers of the asphalt pavement are stable t1 , H b1 ; Step S3, substituting the temperatures measured and calculated in step S1 and step S2 into the temperature decay model obtained by fitting under the watering condition, and estimating the temperature of the upper and lower layers of the asphalt pavement that changes with time after the initial pressure watering; Step S4, based on the upper and lower layer temperatures that change with time after initial compaction and watering, calculate the holographic equivalent temperature that takes into account the asphalt layer depth and compaction time.

2. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 1 is characterized in that: The initial temperature of the lower layer of the asphalt pavement is calculated as follows: weighting the temperature in the layer and the temperature at the bottom of the layer to obtain the initial temperature of the lower layer of the asphalt pavement, wherein the position in the layer is the position of the total thickness of the asphalt layer / 2, and the position at the bottom of the layer is the position of the total thickness of the asphalt layer; The initial temperature calculation method of the lower layer of the asphalt pavement is: Where, T b0 is the initial temperature of the lower layer of the asphalt pavement; Zα α is the quantile of the temperature of the upper and lower layers of the asphalt pavement at the significance level α; T2(t0) and T3(t0) represent the temperature in the layer and the temperature at the bottom of the layer corresponding to the initial paving time t0, respectively.

3. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 2 is characterized in that: The calculation process of the temperature in the layer includes: Calculate the temperature T1(x±(h / 2),y±(h / 2)) at a point h / 2 from the layer surface, specifically: Where h is the total thickness of the asphalt layer, T1(x,y) is the temperature of any point (x,y) in the temperature field of the layer surface plane; Assuming that the natural logarithm of the temperature of points at the same depth or plane direction from the plane point conforms to the normal distribution, the probability density expression of the logarithm of the temperature in the layer corresponding to the center point is; Among them, T2(x,y) is the temperature in the layer; μ2(x,y) is the mean of the probability density function of the logarithmic value of the temperature in the layer; σ2(x,y) is the standard deviation of the probability density function of the logarithmic value of the temperature in the layer.

4. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 2 is characterized in that: The bottom temperature calculation process includes: Calculate the temperature T1(x±h,y±h) of the surface point of the layer at the distance layer surface point h, specifically: Where h is the total thickness of the asphalt layer, T1(x,y) is the temperature of any point (x,y) in the temperature field of the layer surface plane; Assuming that the natural logarithm of the temperature of points at the same depth or plane direction from the plane point conforms to the normal distribution, the probability density expression of the logarithm of the bottom temperature corresponding to the center point is: Among them, T3(x,y) is the bottom temperature; μ3(x,y) is the mean of the probability density function of the logarithmic value of the bottom temperature; σ3(x,y) is the standard deviation of the probability density function of the logarithmic value of the bottom temperature.

5. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 1 is characterized in that: The temperature decay model under the watering condition includes a temperature decay model for the upper layer of the asphalt pavement and a temperature decay model for the lower layer of the asphalt pavement; The fitting process of the temperature decay model under the watering condition is as follows: the initial temperature T of the upper layer of the asphalt pavement collected during the test phase of asphalt pavement construction is t0 , according to the initial temperature T t0 Calculate the initial temperature T of the lower layer of the pavement b0 , and the ambient temperature H when the initial pressure is measured t0 , Sprinkler temperature amplitude ΔT C , the temperature T of the upper and lower layers of the asphalt pavement changing with time t t 、T b The equilibrium temperature H when the temperature changes steadily t1 , H b1 , substituted into the corresponding asphalt pavement upper layer watering temperature decay model and lower layer temperature decay model, fitted the temperature change law over time, and obtained the fitting parameters k in the asphalt pavement upper layer watering temperature decay model respectively. t1 , k t2 , and the fitting parameter k in the lower temperature decay model b1 , k b2 .

6. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 5, characterized in that: The watering temperature decay model of the upper layer of the asphalt pavement is specifically: Where, T t is the temperature of the upper layer of the asphalt pavement changing with time t; T t0 ΔT is the initial temperature of the upper layer of the asphalt pavement when water is initially applied; C H is the variation range of watering temperature; t0 is the ambient temperature during initial compaction; H t1 k is the temperature when the ambient temperature and the pavement temperature tend to be balanced and stable; t1 , k t2 are the fitting parameters in the model.

7. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 5, characterized in that: The temperature decay model of the lower layer of the asphalt pavement is specifically: Where, T b is the temperature of the lower layer of the asphalt pavement changing with time t; T b0 is the initial temperature of the lower layer of the asphalt pavement; H b1 k is the temperature when the lower layer temperature and the pavement temperature tend to be balanced and stable; b1 , k b2 are the fitting parameters in the model.

8. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 1 is characterized in that: The equivalent temperature calculation considering the depth of the asphalt layer is specifically as follows: Where, T s is the equivalent temperature of the asphalt pavement; h1 is the thickness of the upper layer of the asphalt pavement; h2 is the thickness of the lower layer of the asphalt pavement; h is the total thickness of the asphalt pavement, h = h1 + h2; T t and T b They are the temperatures of the upper and lower layers of the pavement changing with time.

9. The method for estimating the holographic equivalent temperature of asphalt pavement compaction according to claim 1, characterized in that: The holographic equivalent temperature calculation considering the compaction time is specifically: Where, T is the holographic equivalent temperature of the asphalt pavement; t1, t2, t3, t4 and t5 are different compaction times respectively; t is the total compaction time, t = t1 + t2 + t3 + t4 + t5; T s1 、T s2 、T s3 、T s4 and T s5 The equivalent temperature of asphalt pavement corresponding to different compaction times.

10. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

Images