CN114675691A - Construction process temperature control method and device for asphalt mixture and storable medium - Google Patents
Construction process temperature control method and device for asphalt mixture and storable medium Download PDFInfo
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Abstract
The invention discloses a construction process temperature control method and device of an asphalt mixture and a storable medium, and relates to the technical field of temperature control, wherein the method comprises the following steps: establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture; after the transportation of the asphalt mixture is completed, acquiring environmental parameters of a construction site, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters; constructing a temperature prediction processor model, and processing the environmental parameters, the pavement temperature model and the construction compaction time model by using the temperature prediction processor model to obtain an optimal construction temperature; collecting the temperature of the asphalt mixture in real time, and adjusting according to the optimal construction temperature; the method can predict the construction temperature of the asphalt mixture under different construction meteorological conditions, and is favorable for guiding construction.
Description
Technical Field
The invention relates to the technical field of temperature control, in particular to a method and a device for controlling the temperature of an asphalt mixture in the construction process and a storable medium.
Background
At present, the asphalt road paving construction process is a process of transporting asphalt mixture from an asphalt production plant to a construction site by an asphalt transport vehicle, then unloading the asphalt mixture onto a paving machine, paving by the paving machine, and finally performing road rolling construction by a road roller.
However, since the return time and state of the transport vehicle cannot be accurately grasped, the constructors cannot know the difference between the delivery temperature distribution of the asphalt mixture and the temperature after transportation, and the temperature condition of the road surface to be constructed, and the construction temperature of the subsequent asphalt mixture cannot be effectively grasped, so that the construction progress is influenced.
Therefore, how to provide a construction process temperature control method of asphalt mixture capable of solving the above problems is a problem that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides a method and a device for controlling the construction process temperature of an asphalt mixture and a storable medium, and the method can predict the construction temperature of the asphalt mixture under different construction meteorological conditions and is favorable for guiding construction.
In order to achieve the purpose, the invention adopts the following technical scheme:
the construction process temperature control method of the asphalt mixture comprises the following steps:
establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
after the transportation of the asphalt mixture is completed, acquiring environmental parameters of a construction site, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
constructing a temperature prediction processor model, and processing the environmental parameters, the pavement temperature model and the construction compaction time model by using the temperature prediction processor model to obtain an optimal construction temperature;
and collecting the temperature of the asphalt mixture in real time, and adjusting according to the optimal construction temperature.
Preferably, the specific process of constructing the temperature prediction processor model comprises the following steps:
setting a constraint condition, wherein the constraint condition comprises: the temperature of the asphalt mixture when the transportation of the asphalt mixture is completed, the weight of the asphalt mixture and the environmental parameters;
constructing the temperature prediction processor model using the constraints, wherein the temperature prediction processor model is a neural network.
Preferably, the specific process for establishing the asphalt mixture construction compaction time model comprises the following steps:
acquiring the real-time temperature of the transported asphalt mixture, and presetting construction parameters of the asphalt mixture;
and establishing the construction compaction time model by considering the modes of heat conduction, convection heat exchange and radiation heat transfer of atmospheric energy transfer and combining the real-time temperature and the construction parameters.
Preferably, the specific process of establishing the transportation temperature model of the asphalt mixture comprises the following steps:
acquiring a transportation scheme of the asphalt mixture, and establishing a simulation model of transportation equipment;
and establishing the transportation temperature model of the asphalt mixture by utilizing finite element analysis software according to the simulation model and combining the delivery temperature of the asphalt mixture and the delivery environment temperature.
Preferably, the specific process of establishing the road surface temperature model includes:
and establishing a quantitative relation between the road surface temperature and the environmental parameters by adopting a statistical regression method according to the road surface temperature and the environmental parameters to obtain the road surface temperature model.
Further, the present invention also provides a control device using any one of the above-described methods for controlling a temperature of an asphalt mixture during a construction process, comprising:
the first construction module is used for establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
the second construction module is used for acquiring the environmental parameters of a construction site after the transportation of the asphalt mixture is completed, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
the processing module is connected with the first building module and the second building module and used for constructing a temperature prediction processor model, and the temperature prediction processor model is used for processing the environmental parameters, the pavement temperature model and the construction compaction time model to obtain the optimal construction temperature;
and the adjusting module is connected with the processing module and is used for acquiring the temperature of the asphalt mixture in real time and adjusting according to the optimal construction temperature.
Further, the present invention also provides a computer-readable storage medium on which a computer program is stored, the computer program, when executed by a processor, implementing the temperature control method according to any one of the above.
Compared with the prior art, the invention discloses a method and a device for controlling the temperature of the asphalt mixture in the construction process and a storable medium, and has the following beneficial effects:
(1) by establishing a transportation temperature model of the asphalt mixture, the transportation temperature model can help asphalt building material enterprises comprehensively consider factors such as transportation road conditions and transportation environments of the asphalt mixture, and control the delivery temperature of products in the production process of the asphalt mixture;
(2) by establishing a pavement temperature model, the actual pavement condition can be accurately simulated and analyzed, and a foundation is provided for subsequent construction;
(3) the temperature prediction processor model is constructed, and the environmental parameters, the pavement temperature model and the construction compaction time model are processed by the temperature prediction processor model to obtain the optimal construction temperature, so that the temperature change condition of the asphalt mixture in the transportation process can be judged in an auxiliary manner, and a theoretical basis is provided for the subsequent paving operation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is an overall flow chart of a construction process temperature control method for an asphalt mixture according to the present invention;
FIG. 2 is a schematic block diagram of a temperature control device for a construction process of an asphalt mixture according to the present invention;
FIG. 3 is a diagram illustrating a variation law of thermal diffusivity with temperature according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a rule of influence of porosity on thermal diffusivity provided by an embodiment of the present invention;
FIG. 5 is a graph illustrating the effect of thickness of a paving layer on temperature of the paving layer according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating the influence of wind speed on the temperature of a spreading layer according to an embodiment of the present invention;
fig. 7 is a diagram illustrating the influence of the temperature of the underlying layer on the temperature of the spreading layer according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to the attached drawing 1, the embodiment of the invention discloses a temperature control method for a construction process of an asphalt mixture, which comprises the following steps:
establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
wherein the asphalt mixture is prepared by mixing coarse and fine aggregates, warm mixing materials and asphalt in a proper proportion.
After the transportation of the asphalt mixture is completed, acquiring environmental parameters of a construction site, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
wherein, the environmental parameter may be: air temperature, humidity, and wind speed;
constructing a temperature prediction processor model, and processing the environmental parameters, the pavement temperature model and the construction compaction time model by using the temperature prediction processor model to obtain the optimal construction temperature;
and collecting the temperature of the asphalt mixture in real time, and adjusting according to the optimal construction temperature.
In a specific embodiment, the specific process of constructing the temperature prediction processor model comprises:
setting a constraint condition, wherein the constraint condition comprises: the temperature of the asphalt mixture when the transportation of the asphalt mixture is completed, the weight of the asphalt mixture and environmental parameters;
and constructing a temperature prediction processor model by using the constraint conditions, wherein the temperature prediction processor model is a neural network.
In a specific embodiment, the specific process of establishing the compaction time model for asphalt mixture construction comprises the following steps:
acquiring the real-time temperature of the transported asphalt mixture, and presetting construction parameters of the asphalt mixture;
the method considers the modes of heat conduction, convection heat exchange and radiation heat transfer of atmospheric energy transfer, combines real-time temperature and construction parameters, establishes a construction compaction time model, can obtain the final compaction time of the asphalt mixture, and is convenient for subsequent control.
Specifically, the specific process of establishing the construction compaction time model may include:
(1) measurement of thermal parameters of asphalt mixture
1. In the embodiment of the invention, the road character coefficient of the asphalt mixture can be measured based on the unsteady state transient heat conduction principle, and the specific derivation process is as follows:
a small time step is chosen to model its linear relationship. Namely: firstly, in each time step, solving the average temperature of a test piece; in each time interval, a linear relationship of the average temperature with time is found. Assume that:
T＝b1t+b2 (1)
in the formula: b1、b2-a first order curve fitting constant;
assuming that the temperature and depth read in each time step are quadratic, the assumption is that:
T＝a1z2+a2z+a3 (2)
in the formula: a is a1、a2、a3-a second order curve fitting constant;
according to the z-direction temperature change formula:
the rearrangement comprises the following steps:
according to formula (1) there are:
according to formula (1) there are:
the thermal conductivity coefficient can be obtained by substituting the formula (5) and the formula (6) for the formula (4)
2. Heat conduction test
The method comprises the steps of carrying out forming treatment on the asphalt mixture to be tested, then carrying out temperature conduction test to obtain a corresponding temperature change curve, and referring to the attached drawings 3-4 as a result, wherein the initial temperature of the surface of an asphalt mixture test piece is very high, the asphalt mixture test piece begins to cool after contacting air, but the temperature of the middle and lower layer can not be influenced by the air temperature in a short time, and therefore, the temperature of the surface layer is firstly reduced and is reduced faster than that of the middle and lower layer. Along with the temperature of the surface layer is decreased more and more, the temperature difference between the middle and lower layers and the surface layer is gradually increased, the temperature is inevitably consistent under the action of heat conduction, the middle and lower layers transfer heat upwards, and the heat transfer rate in the process is the temperature conduction coefficient. Within the temperature of the test piece of 60-160 ℃, the temperature of the surface layer is reduced quickly, and the temperature difference between the upper part and the middle-lower part of the test piece is increased, so that the upward heat transfer speed of the middle layer is increased, namely the temperature conductivity coefficient of the test piece is increased along with the reduction of the temperature within 60-160 ℃.
In addition, the void ratio greatly affects the thermal conductivity. Due to the influence of factors such as test stability, change uniformity of a temperature field and the like, the obtained temperature conduction coefficient has larger result dispersion at the early stage and the last stage of the test, and for convenience of comparison, data at the middle stage of the test is intercepted, namely 20-100 min, and the corresponding temperature is about the cooling process of 140-100 ℃. In the interval, the variation range of the thermal conductivity coefficient of the asphalt mixture test piece with the porosity of 7.2 percent is 2.20E 06-3.50E-06 m2The temperature conductivity coefficient change range of an asphalt mixture test piece with 11.8% of void ratio is 2.50E-06-3.00E-06 m2The temperature coefficient of thermal conductivity of the test piece with the porosity of 18.3 percent is within the range of 0.80E-06-1.2E-06 m2The thermal conductivity coefficient of the test piece with the porosity of 5.8 percent is about 0.90E-06m2And s. It can be found that the obtained thermal conductivity coefficients of the two test pieces with the minimum porosity and the maximum porosity are relatively close and relatively small. This is because the thermal diffusivity of the material is reflected in the thermal coefficient, that is, the temperature difference at each point inside the object is smaller when the thermal coefficient is larger, and the temperature difference at each point inside the object is larger when the thermal coefficient is smaller. For the test piece with the minimum porosity, although the overall average cooling of the test piece is slower, the cooling of the surface layer of the test piece is still faster, and due to the high density, the cooling of the surface layer cannot be quickly transferred to the bottom layer, so that the temperature difference between the surface layer and the bottom layer is larger, and the temperature conductivity coefficient is relatively smaller; for the test piece with the largest porosity, the temperature reduction rate and the amplitude of the surface layer are obviously greater than those of the bottom layer, and the temperature field is also larger in nonuniformity, so that the temperature conductivity coefficient is smaller; in contrast, the test pieces with the porosity of 7.2% and 11.8% have more uniform temperature reduction and more uniform temperature difference of each part, thereby showing larger thermal conductivity coefficient.
(2) Temperature model finite element analysis in asphalt mixture construction process
The reference pavement structure of this analysis was 4cm thick on the top, 5cm thick on the middle, and 6cm thick on the bottom. The air temperature is 30 ℃, the temperature of the lower lying layer is 15 ℃, and the wind speed is 10 m/s. The influence of the thickness change of the upper layer, the temperature change of air, the temperature change of the lower lying layer and the wind speed change on the temperature field in the paving process is discussed respectively. The material parameters are given in table 1 below.
TABLE 1 Material parameter Table
The embodiment of the invention adopts large-scale general finite element software ANSYS to carry out numerical simulation, applies a thermodynamic analysis module thereof and applies transient boundary load by a programming method. A solid70 unit is adopted to simulate a road surface structure, and a surf152 unit is adopted to apply convection load to the road surface. Boundary conditions include thermal convection, solar radiation, and long wave radiation. The solar radiation is converted into heat flux density according to parameters such as solar altitude, solar azimuth, pavement azimuth and the like and is applied to the surface layer unit, and the specific analysis result is as follows:
1. sensitive analysis of spreading layer thickness
On the basis of a reference structure, five working conditions of 3cm, 4cm, 5cm, 6cm and 7cm of upper layer thickness are adopted for analysis. The temperature distribution curve of the cross section of the spreading layer is shown in figure 5; the heat preservation effect of different spreading layer thicknesses is different, and the thicker the spreading layer is, the better the heat preservation effect is. The thickness of the constant temperature field is from 0.3 to 0.7 from the surface ratio for a layer thickness of 3cm and from 0.1 to 0.9 from the surface for a layer thickness of 7 cm. The constant temperature field ratio doubles. The temperature of each layer of the surface layer has no obvious change along with the increase of the paving thickness, and the temperature of the middle layer and the middle layer of the surface layer are the same and are in a stable state of 16 ℃. The temperature of the upper surface of the surface layer exhibits a saw-toothed variation due to the sprinkling of the roller and the heat exchange with the middle surface of the upper surface layer of the surface layer. The thickness of the paving layer only influences the heat preservation effect of the surface layer, and does not influence the temperature rise and fall of each surface layer of the surface layer.
2. Sensitive analysis of wind speed
On the basis of a reference structure, the temperature at different depths of the same point is analyzed by adopting four working conditions with the wind speeds of 10m/s, 20m/s, 30m/s and 40m/s respectively. The temperature distribution curve of the cross section of the spreading layer is shown in FIG. 6, the temperature of the spreading layer drops more rapidly when the wind speed is larger, the surface temperature of the spreading layer drops to nearly 15 ℃ in the same time when the wind speed is increased by 10m/s, and the temperature of the bottom of the spreading layer also drops to a certain extent, but the temperature drop speed is not as fast as the surface drop speed. From the temperature of the whole spreading layer, the larger the wind speed is, the faster the temperature drops in the same time, the surface heat dissipation is fastest, the bottom temperature drops slowly, and the temperature in the middle of the spreading layer is kept in a stable state, which is mainly because the larger the wind speed is, the heat exchange between the surface and the air is accelerated, the temperature curve gradually develops from symmetry to asymmetry, and therefore, the temperature of a lying layer has an important effect on the temperature of the spreading layer in the case of windy weather; the trend that the surface temperature of the upper layer of the surface layer is reduced along with the increase of the wind speed is larger, and the temperature is reduced by 13 ℃ every time the wind speed is increased by 10m/s, so that attention should be paid to a road roller following a paver under windy conditions to prevent the road roller from hardening and crusting too fast due to temperature loss and being difficult to roll. And the surface temperature of the upper layer of the surface layer shows zigzag change due to the sprinkling of the road roller and the heat exchange with the middle surface of the upper layer of the surface layer. The wind speed increase has little influence on the middle surface of the upper layer of the surface layer, while the bottom surface of the upper layer of the surface layer has a trend of decreasing with the increase of the wind speed, but the change is not big, and the temperature decreases by 7 ℃ every 10m/s of the increase of the wind speed, which is mainly caused by the temperature change of the lower lying layer. The middle surface of the surface layer and the middle surface of the lower layer have small sensitivity to wind speed due to the fact that the middle surface of the surface layer and the middle surface of the lower layer are far away from the surface of the surface layer, and the sensitivity to wind speed is basically the same.
3. Sensitive analysis of temperature of the underlying layer
On the basis of a reference structure, five working conditions of 15 ℃, 25 ℃, 35 ℃, 45 ℃ and 55 ℃ of the temperature of the lower lying layer are adopted for analysis. The temperature distribution curve of the cross section of the spreading layer is obtained and is shown in fig. 7, the thickness of the lower lying layer mainly influences the temperature of the bottom of the spreading layer, the temperature of the bottom of the spreading layer is higher as the temperature of the lower lying layer is higher, and the temperature of the surface and the middle surface of the spreading layer is basically not changed, because the bottom of the spreading layer is directly contacted with the lower lying layer for heat conduction. The temperature of the lying layer has no obvious influence on the temperature of the upper surface and the middle surface of the surface layer, and the temperature of the upper surface of the surface layer shows zigzag change due to the sprinkling of the road roller and the heat exchange with the middle surface of the upper surface of the surface layer. The upper bottom surface of the surface layer slightly rises along with the rise of the temperature of the lower lying layer, the middle surface of the middle layer and the middle surface of the lower layer of the surface layer obviously rise, the temperature of the upper bottom surface rises by about 3 ℃ when the temperature of the lower lying layer rises by 10 ℃, and the middle surface of the middle layer and the middle surface of the lower layer of the surface layer rise by 10 ℃. This is mainly due to the temperature of the layers lying below.
(3) Ash correlation analysis of influence factors of cooling rate of asphalt mixture
The factors influencing the warm-mixed asphalt mixture are more. In order to avoid the defects existing in the multi-factor analysis by a mathematical statistics method, the influence factors of the cooling rate of the warm-mixed asphalt mixture of the test road are analyzed by a grey correlation analysis method. The grey correlation analysis is a multi-factor statistical analysis method, and on the basis of sample data of various factors, the grey correlation degree is used for describing the strength, the size and the sequence of the relationship among the factors. If the sample data column reflects that the trend of the change of the two factors is basically consistent, the relevance between the sample data column and the two factors is large; otherwise, the degree of association is small. The grey correlation analysis has low requirement on data and small calculation amount, and is suitable for application under the similar research conditions.
The main factors influencing the temperature change of the asphalt pavement material include: layer thickness, wind speed, atmospheric temperature, subnatal layer temperature, solar radiation (cloud), etc. The research makes statistics on the factors in the warm-mixed asphalt mixture construction process, and calculates the cooling rate under each working condition according to the previous method. The results are shown in Table 2
TABLE 2 Cooling Rate of Warm-mix asphalt mixtures under various external conditions
1. Construction of analytical arrays
The results of the calculation of the cooling rate of the warm-mix asphalt mixture under different external conditions in table 1 were used as the original number series. The layer thickness, wind speed, air temperature, sub-layer temperature and cloud layer coefficient in the table constitute a comparison sequence, and the cooling rate constitutes a reference sequence. From the comparison of the sequences with the reference sequences, the following matrix can be formed
2. Dimensionless influence factor and cooling rate
And carrying out dimensionless processing on the original data by using an averaging method. Dimensionless matrix
3. Calculating proximity
According to delta0i(k)＝|x0(k)-xi(k) Calculating to obtain a difference sequence to obtain an absolute difference matrix of the cooling rate and other factors
From the absolute difference matrix result, the minimum difference Δ min is 0.00 and the maximum difference Δ max is 2.2344 in the correlation analysis of the external factors and the cooling rate.
4. Calculating the degree of association
Substituting the proximity value, the maximum difference value and the minimum difference value into a formula
And calculating a correlation coefficient between the external factor and the cooling rate. The calculated correlation coefficient is brought into a formula
Obtaining external factors and cooling rateThe correlation degrees between the two are respectively as follows: r is1＝0.5288，r2＝0.4362，r3＝0.4234，r4＝0.3135，r5＝0.2398。
5. Analysis of results
According to the relevance analysis result, the relevance ranking of the influence of external factors on the cooling rate of the warm-mixed asphalt mixture is as follows: layer thickness, wind speed, sub-layer temperature, air temperature and cloud layer distribution.
The relationship between the thickness of the asphalt surface layer and the cooling rate of the mixture is the largest, mainly because the heat gradually dissipated in the paving and rolling process of the hot-mix asphalt mixture surface layer enables the air near the surface of the mixture to form a higher temperature area, the formation of the high temperature area plays a role in shielding the excessive dissipation of the heat, once the hot air shielding area is formed, the normal temperature area in the external environment is far away from the mixture, and therefore the heat of the hot-mix mixture is protected. When the asphalt surface layer is thicker, the shielding effect is more obvious, so that the influence of the lower temperature of the mixture on the mixture is temporarily weakened, and the mixture is gradually lost at a slower speed.
The reason that the air speed has obvious effect on the cooling rate of the mixture is that the air is the natural convection phenomenon of the air, and the influence of the air mainly can promote the air to flow and accelerate the heat transfer. If the high temperature air shielded area formed near the surface of the paving layer is relatively stable and complete under the condition of no wind or small wind force, the heat transferred to the air by the hot-mix is less, and the temperature of the mix is reduced at a lower speed. It should be noted that if the wind blows continuously, the air above the spreading layer always keeps at a temperature similar to the atmospheric air, and the temperature difference between the surface of the spreading layer and the upper air is always large, so that the mixture transfers much heat to the air through heat conduction, and therefore, the influence of the wind force on the temperature field is great. And the influence of wind cooling can cause the surface of the mixed material to generate a hard shell surface, the thickness of the hard shell surface is generally 1-1.3 cm, and the hard shell surface can cause heat crack of the pavement under the rolling action of a rigid wheel road roller, so that the future service life of the asphalt pavement is seriously influenced. Therefore, in the case of high wind speed, the rolling time should be taken to avoid affecting the engineering quality.
The relationship between the temperature of the underlying layer and the cooling rate of the mixture is centered, and the main reason is that the temperature gradient exists between the middle of the surface layer and the top surface and the bottom surface of the surface layer, and along with the reduction of the temperature of the top surface and the bottom surface of the surface layer, more heat is transferred to the upper side and the lower side in the middle of the surface layer containing higher temperature, so that the temperature of the intermediate point of the surface layer is greatly reduced.
The main reason for analyzing the relationship between the air temperature and the cooling rate of the mixture is that when the temperature of the external ambient environment is low, the ambient air and the temperature of the underlying layer are both low, and when the high-temperature mixture is spread, the temperature gradient between the top surface and the bottom surface of the surface layer and the ambient environment is large, so that the heat transferred to the ambient environment and the intermediate surface layer through convection and conduction is large, and the temperature of the mixture is reduced quickly.
The relation between the cloud layer distribution condition and the mixture cooling rate is the minimum, the main reason is that the cloud layer distribution condition can influence the solar radiation amount on the surface of the asphalt mixture, and the solar radiation amount is difficult to rapidly gather in the short paving and compacting processes of the asphalt pavement, so that the temperature influence in the paving process of the asphalt mixture is not obvious as that in the using process.
(4) The asphalt mixture compaction time based on fuzzy analysis comprises the following specific processes:
1. fuzzy variables can be classified according to their nature as follows: the air temperature, the paving temperature and the initial pressure temperature can be divided into very low, moderate, high and very high; the wind speed is divided into small, large and large; the thickness of the surface layer is divided into: thin, normal, thick; the compacting time is divided into very short, normal, long. Respectively expressed as: air temperature (T)l、Tle、Tm、Tup、Th) Wind speed (W)s、Wse、Wbe、Wb) Thickness of surface layer (L)Tw、LTm、LTt) Temperature of spreading (PT)l、PTle、PTm、PTup、PTh) Initial pressure temperature (IT)l、ITle、ITm、ITup、ITh) Compaction time (C)TMvs、CTMs、CTMrs、CTMm、CTMrl、CTMl、CTMvl) The general detection range is 0 to 30 ℃, and the detection range is divided into five grades according to needs, and the five grades are respectively represented by five values of 0, 1, 2, 3 and 4 (in the fuzzy analysis, the grade is called as a "domain of discourse"), and the calculation of the values is shown in table 3.
TABLE 3 fuzzy input variable fuzzification and its universe of discourse table
Knowing the domain to which the variable input value belongs, i.e. determining the relationship between the variable domain and the fuzzy set of variables, the relationship is a fuzzy membership function (argument is domain and dependent variable is degree of membership). The meaning of such a function is: the probability of the domain belongs to the elements in the fuzzy concentration of the air temperature (for example, the air temperature is 30 ℃ and belongs to the domain 4, the domain has 100% probability of belonging to the high air temperature, 60% probability of belonging to the high air temperature, 0% probability of belonging to the moderate air temperature, 0% probability of belonging to the low air temperature and 0% probability of belonging to the low air temperature); how this probability (in the fuzzy approach, called membership) is determined, i.e. how the membership function is determined. The method is more, and the method is mainly obtained according to experience and relevant data. The results are shown as fuzzy variables (tables 4-9). The fuzzy input variables can be fuzzified and the output variables can be deblurred according to tables 4-9.
TABLE 4 fuzzy input variable fuzzification and its universe of discourse table
TABLE 5 fuzzy input variable fuzzification and its universe of discourse table
TABLE 6 fuzzy input variable fuzzification and its universe of discourse table
TABLE 7 fuzzy input variable fuzzification and its universe of discourse table
TABLE 8 fuzzy input variable fuzzification and its universe of discourse table
TABLE 9 fuzzy input variable fuzzification and its universe of discourse table
(2) Establishment of fuzzy inference rule
1. The fuzzy inference rules are as follows:
11. the effective compaction time increases rapidly with increasing air temperature, and decreases rapidly with decreasing air temperature, particularly at temperatures below 10 ℃.
12. The influence of the initial pressing temperature on the compaction time conforms to a logarithmic function relationship, namely the thicker the surface layer thickness is, the longer the compaction time is.
13. The cooling rate of the mixture can be effectively reduced and the effective compaction time can be prolonged by increasing the thickness of the surface layer.
14. With increasing wind power, the effective compaction time is reduced, and particularly when the wind power is greater than 3 levels, the mix cooling rate is increased significantly.
15. If the air temperature is very low, the surface layer thickness is common, the wind power is very small, the paving temperature is very high and the initial pressing temperature is very high, the effective compaction time is very short.
16. If the air temperature is very low, the surface layer thickness is common, the wind power is very small, the paving temperature is low and the initial pressing temperature is very low, the effective compaction time is short.
17. If the air temperature is moderate, the surface layer thickness is general, the wind power is small, the paving temperature is high and the initial pressing temperature is moderate, the effective compacting time is general.
18. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low and the initial pressing temperature is moderate, the effective compacting time is long.
19. If the air temperature is very high, the surface layer thickness is common, the wind power is very small, the paving temperature is low and the initial pressing temperature is very low, the effective compaction time is very long.
110. If the air temperature is high, the surface layer thickness is thin, the wind power is small, the paving temperature is moderate, and the initial pressing temperature is low, the effective compaction time is short.
111. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low, and the initial compaction temperature is low, the effective compaction time is long.
112. If the air temperature is high, the surface layer thickness is thick, the wind power is low, the paving temperature is low and the initial pressing temperature is low, the effective compaction time is long.
113. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low, and the initial pressing temperature is low, the effective compaction time is long.
114. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low, and the initial pressing temperature is low, the effective compaction time is long.
115. If the air temperature is high, the surface layer thickness is general, the wind power is large, the paving temperature is moderate, and the initial pressing temperature is low, the effective compacting time is general.
116. If the air temperature is high, the surface layer thickness is general, the wind power is high, the paving temperature is moderate, and the initial pressing temperature is low, the effective compaction time is short.
117. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low, and the initial pressing temperature is low, the effective compacting time is long.
118. If the air temperature is high, the surface layer thickness is general, the wind power is small, the paving temperature is low and the initial pressing temperature is low, the effective compacting time is general.
The corresponding fuzzy relation equation can be obtained according to the fuzzy inference rule
R1＝(T1×CTMvs)(LTm×CTmvs)(Ws×CTMvs)(PTh×CTMvs)(ITh×CTMvs)
If the actual measurement results in the above definite value of the input fuzzy variable being T1、W1、LT1、PT1、IT1. Obtaining the corresponding theory domain value of each variable by looking up the theory domain table of the fuzzy input variable, and then querying the fuzzy variable value-assigning table to obtain the fuzzy vector value T of each input variable11、W11、LT11、PT11、IT11Finding the corresponding output value
CTM1＝T11(T1×CTMvs)W11(LTm×CTMVS)·LT11(Ws×CTMvs)PT11(PTh×CTMvs)·I11(ITh×CTMvs)
Similarly, the corresponding output values C can be respectively obtained by the other fuzzy relation equationsTM2、CTM3…，CTM14。
CTM＝CTM1+CTM2+…+CTM14
The calculated fuzzy vector value is converted into an accurate value through a fuzzy solving method. The deblurring method employed here is the method of maximum membership.
2. Determination of effective compaction time
Suppose at 7In the construction of the cm asphalt layer (the temperature is 15 ℃, the wind power is 2 grade, the weather is clear, the paving temperature is 140 ℃, the initial pressure temperature is 130 ℃), and the fuzzy vector T of each input variable is obtained by inquiring the fuzzy variable assignment table11、W11、LT11、PT11、IT11。
T11＝{0.2,0.6,1.0,0.6,0.2}
W11＝{1.0,0.5,0.0,0.0}
LT11＝{0.7,1.0,0.1}
PT11＝{0.0,0.3,0.6,1.0,0.6}
IT11＝{0.2,0.6,1.0,0.6,0.2}
Bring it into CTM1In the formula
CTM1＝{0.00,0.10,0.40,0.60,0.95,0.60,0.4,0.10,0.00}
Obtaining C according to other fuzzy relation equations in the same wayTM2、CTM3…、CTM14And summing the values to obtain:
CTM＝{0.00,0.10,0.30,0.70,1.0,0.60,0.4,0.10}
deblurring the maximum membership
CTM＝{0.00,0.00,0.00,0.00,1.0,0.00,0.0,0.00}
And 3, looking up a table, wherein the effective compaction time is 33-35 min.
The application of the fuzzy analysis method for the effective compaction time of the asphalt mixture shows that the method can basically meet the requirements of surface layer construction. Especially, when the temperature is lower than 20 ℃ or other environmental conditions are severe (such as high wind power, rainy days and the like), the prediction of the effective compaction time of the asphalt mixture has important significance. And when the environmental conditions are good (such as high air temperature and the like) and the surface layer is thick, the compaction time of the asphalt mixture can meet the requirement of normal rolling operation.
In a specific embodiment, the specific process of establishing the transportation temperature model of the asphalt mixture comprises the following steps:
acquiring a transportation scheme of the asphalt mixture, and establishing a simulation model of transportation equipment;
and establishing a transportation temperature model of the asphalt mixture by utilizing finite element analysis software according to the simulation model and combining the delivery temperature of the asphalt mixture and the delivery environment temperature.
In one specific embodiment, the specific process of establishing the road surface temperature model includes:
and establishing a quantitative relation between the road surface temperature and the environmental parameters by adopting a statistical regression method according to the road surface temperature and the environmental parameters to form a road surface temperature model.
Referring to fig. 2, an embodiment of the present invention further provides a control device for a construction process temperature control method using an asphalt mixture according to any one of the above embodiments, including:
the first construction module is used for establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
the second construction module is used for acquiring the environmental parameters of a construction site after the transportation of the asphalt mixture is completed, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
the processing module is connected with the first building module and the second building module and used for constructing a temperature prediction processor model, and the temperature prediction processor model is used for processing the environmental parameters, the pavement temperature model and the construction compaction time model to obtain the optimal construction temperature;
and the adjusting module is connected with the processing module and is used for acquiring the temperature of the asphalt mixture in real time and adjusting according to the optimal construction temperature.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the temperature control method in any one of the above embodiments is implemented.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A construction process temperature control method of an asphalt mixture is characterized by comprising the following steps:
establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
after the transportation of the asphalt mixture is completed, acquiring environmental parameters of a construction site, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
constructing a temperature prediction processor model, and processing the environmental parameters, the pavement temperature model and the construction compaction time model by using the temperature prediction processor model to obtain an optimal construction temperature;
and collecting the temperature of the asphalt mixture in real time, and adjusting according to the optimal construction temperature.
2. The method for controlling the construction process temperature of the asphalt mixture according to claim 1, wherein the specific process of constructing the temperature prediction processor model comprises the following steps:
setting a constraint condition, wherein the constraint condition comprises: the temperature of the asphalt mixture when the transportation of the asphalt mixture is completed, the weight of the asphalt mixture and the environmental parameters;
constructing the temperature prediction processor model using the constraints, wherein the temperature prediction processor model is a neural network.
3. The method for controlling the construction process temperature of the asphalt mixture according to claim 2, wherein the specific process of establishing the asphalt mixture construction compaction time model comprises the following steps:
acquiring the real-time temperature of the transported asphalt mixture, and presetting construction parameters of the asphalt mixture;
and establishing the construction compaction time model by considering the modes of heat conduction, convection heat exchange and radiation heat transfer of atmospheric energy transfer and combining the real-time temperature and the construction parameters.
4. The method for controlling the construction process temperature of the asphalt mixture according to claim 3, wherein the specific process of establishing the transportation temperature model of the asphalt mixture comprises the following steps:
acquiring a transportation scheme of the asphalt mixture, and establishing a simulation model of transportation equipment;
and establishing the transportation temperature model of the asphalt mixture by utilizing finite element analysis software according to the simulation model and combining the delivery temperature of the asphalt mixture and the delivery environment temperature.
5. The method for controlling the construction process temperature of the asphalt mixture according to claim 1, wherein the concrete process of establishing the pavement temperature model comprises the following steps:
and establishing a quantitative relation between the road surface temperature and the environmental parameters by adopting a statistical regression method according to the road surface temperature and the environmental parameters to obtain the road surface temperature model.
6. A control device for a construction process temperature control method using an asphalt mixture according to any one of claims 1 to 5, comprising:
the first construction module is used for establishing a transportation temperature model of the asphalt mixture according to the delivery temperature of the asphalt mixture;
the second construction module is used for acquiring the environmental parameters of a construction site after the transportation of the asphalt mixture is completed, and establishing a pavement temperature model and a construction compaction time model according to the environmental parameters;
the processing module is connected with the first building module and the second building module and used for constructing a temperature prediction processor model, and the temperature prediction processor model is used for processing the environmental parameters, the pavement temperature model and the construction compaction time model to obtain the optimal construction temperature;
and the adjusting module is connected with the processing module and is used for acquiring the temperature of the asphalt mixture in real time and adjusting according to the optimal construction temperature.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a temperature control method according to any one of claims 1 to 5.
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