Method, prediction method and device for obtaining milling particle size distribution prediction model

Abstract

The present disclosure provides a method, a prediction method and a device for obtaining a milling particle gradation prediction model. The method includes: after a milling test on an asphalt layer, screening multiple groups of test particles obtained through the milling test to obtain the proportion of the remaining mass corresponding to each of multiple sieves, wherein each group of test conditions in the multiple groups of test conditions includes: the rotation speed, the forward speed and the milling depth of the milling rotor of the in-situ cold recycling equipment, and the multiple sieves have different aperture specifications; calculating characteristic parameters of the cutting pattern of the milling rotor according to the tooth arrangement pattern, the rotation speed, the forward speed and the milling depth of the milling rotor; establishing a functional relationship between the proportion of the remaining mass corresponding to each sieve obtained through the milling test and the characteristic parameters of the cutting pattern of the milling rotor through regression analysis according to the rotation speed, the forward speed and the milling depth; and performing normalization processing on the functional relationship to obtain the milling particle gradation prediction model.

Description

Technical Field

[0001] The present disclosure relates to the technical field of highway pavement maintenance construction, and particularly relates to a method, a prediction method, and a device for obtaining a milling particle gradation prediction model. Background Art

[0002] In-situ cold recycling is a technology that uses special equipment to mill the asphalt layer of the pavement in-situ, incorporates a certain amount of new mineral materials, recycling binders, water, etc., and realizes the recycling of the old asphalt pavement in one step through processes such as normal-temperature mixing, paving, and compaction. In the in-situ cold recycling technology, the old materials obtained from the asphalt pavement by milling, excavation, etc. are the asphalt pavement recycled materials.

[0003] Gradation is the distribution of particles of each particle size of the aggregate, which can be determined by a sieve analysis test. Gradation calculation method: (1) Percentage of individual sieve residue: The percentage of the sieve residue mass on a certain sieve in the total mass of the sample; (2) Cumulative sieve residue percentage: The sum of the percentage of individual sieve residue on a certain sieve and the percentages of individual sieve residues on sieves larger than that certain sieve; (3) Percentage passing: The percentage of the mass passing through a certain sieve in the total mass of the sample.

[0004] Currently, the renovation and reuse of old pavements have become the key tasks of pavement maintenance work. The asphalt recycling process system includes two construction processes: in-situ cold recycling and full-depth cold recycling. One of the requirements for in-situ cold recycling construction of the asphalt layer is that the recycled asphalt particles meet a certain gradation combination.

[0005] In the related art, section recycling tests can be carried out to analyze and obtain the particle size gradation of the recycled particles. This often requires conducting multiple groups of section recycling tests to determine the combination of operating parameters that meet the construction requirements. This leads to cumbersome operation tasks and long test times, and further leads to long construction times. In addition, the above process may also cause problems such as waste of asphalt layer materials. Summary of the Invention

[0006] One technical problem solved by the present disclosure is to provide a method for obtaining a milling particle gradation prediction model, so as to facilitate the prediction of the recycled particle gradation and shorten the construction time.

[0007] According to one aspect of the present disclosure, a method for obtaining a milling particle gradation prediction model is provided, including: after performing milling tests on the asphalt layer under respectively set multiple groups of test conditions, screening multiple groups of test particles obtained through the milling tests to obtain the proportion of the remaining mass corresponding to each sieve among multiple sieves, wherein each group of test conditions in the multiple groups of test conditions includes: the rotational speed, the forward speed, and the milling depth of the milling rotor of the in-situ cold recycling equipment, and the multiple sieves have different aperture specifications; calculating characteristic parameters of the cutting pattern of the milling rotor according to the tooth arrangement pattern of the milling rotor, the rotational speed, the forward speed, and the milling depth; establishing a functional relationship between the proportion of the remaining mass corresponding to each sieve obtained through the milling test and the characteristic parameters of the cutting pattern of the milling rotor through regression analysis according to the rotational speed, the forward speed, and the milling depth, wherein the proportion of the remaining mass corresponding to each sieve is a function of the characteristic parameters of the cutting pattern of the milling rotor; and normalizing the functional relationship to obtain a milling particle gradation prediction model.

[0008] In some embodiments, calculating the characteristic parameters of the cutting pattern of the milling rotor according to the tooth arrangement pattern of the milling rotor, the rotational speed, the forward speed, and the milling depth includes: calculating the position when the x-th tooth of the milling rotor passes through the maximum milling thickness according to the tooth arrangement pattern of the milling rotor, the rotational speed, the forward speed, and the milling depth, where x is a positive integer and x > 1; calculating the equation expression of the breakage line corresponding to the x-th tooth according to the position when the x-th tooth of the milling rotor passes through the maximum milling thickness and the breakage angle when the x-th tooth mills the asphalt layer, so as to obtain the equation expressions of the breakage lines corresponding to multiple teeth of the milling rotor, and the multiple teeth include the x-th tooth; and calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th tooth according to the equation expressions of the breakage lines corresponding to multiple teeth of the milling rotor and the cutting pattern of the milling rotor, as the characteristic parameters of the cutting pattern of the milling rotor.

[0009] In some embodiments, the position when the x-th tooth of the milling rotor passes through the maximum milling thickness is the coordinate (L x , P x ), where L x is the abscissa of the x-th tooth in the direction parallel to the axis of the milling rotor in the cutting pattern, and the L x is a known quantity; P x is the ordinate of the x-th tooth in the direction perpendicular to the axis of the milling rotor in the cutting pattern, wherein, wherein, Cx x is the circumferential angle of the x-th cutting tooth, v is the forward speed of the milling rotor, n is the rotational speed of the milling rotor, H is the milling depth, R is the milling radius of the milling rotor, m is the number of complete rotations that the x-th cutting tooth has made, m≥0 and m is an integer.

[0010] In some embodiments, based on the equation expressions of the spalling lines corresponding to multiple cutting teeth of the milling rotor and the cutting diagram of the milling rotor, the characteristic parameters of the cutting unit pattern corresponding to the x-th cutting tooth are calculated as follows: obtaining the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th cutting tooth according to the equation expressions of the spalling lines corresponding to multiple cutting teeth of the milling rotor; calculating the position coordinates of multiple vertices of the cutting unit pattern corresponding to the x-th cutting tooth according to the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th cutting tooth; and calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th cutting tooth according to the position coordinates of the multiple vertices.

[0011] In some embodiments, the characteristic parameter of the cutting unit pattern corresponding to the x-th cutting tooth is: the length of the hypotenuse of a right triangle constructed inside the cutting unit pattern with one side of the cutting unit pattern as a right side according to a predetermined composition method.

[0012] In some embodiments, the functional relationship between the percentage of the residue mass corresponding to each sieve and the characteristic parameters of the cutting diagram of the milling rotor is where is the percentage of the residue mass of the -th sieve, τ is the characteristic parameter of the cutting diagram of the milling rotor, and are coefficients.

[0013] In some embodiments, the normalization process for the functional relationship includes: calculating the theoretical values of the percentage of the residue mass corresponding to each sieve of multiple sieves according to the characteristic parameters of the cutting diagram of the milling rotor and the functional relationship; calculating the sum of the theoretical values of the percentage of the residue mass corresponding to the multiple sieves according to the theoretical values of the percentage of the residue mass corresponding to each sieve; and using the sum of the theoretical values of the percentage of the residue mass corresponding to the multiple sieves to perform normalization on the functional relationship.

[0014] In some embodiments, the milling rotor includes: a drum; and multiple rows of cutter teeth spirally arranged on the drum, wherein the arrangement of the cutter teeth of the milling rotor is such that the multiple rows of cutter teeth include a plurality of cutter tooth groups, and the plurality of cutter tooth groups are arranged along the axial direction of the drum; wherein each cutter tooth group includes a first cutter tooth, a second cutter tooth, and a third cutter tooth, the first cutter tooth, the second cutter tooth, and the third cutter tooth are respectively located in different rows of the multiple rows of cutter teeth, the projection of the second cutter tooth on the axis of the drum is located between the projection of the first cutter tooth on the axis of the drum and the projection of the third cutter tooth on the axis of the drum, and the difference between the circumferential angle of the third cutter tooth and the circumferential angle of the first cutter tooth is less than the difference between the circumferential angle of the second cutter tooth and the circumferential angle of the first cutter tooth.

[0015] In some embodiments, during the process of milling the asphalt layer by using the milling rotor, the asphalt layer is cut in the order of the first cutter tooth, the third cutter tooth, and the second cutter tooth.

[0016] According to another aspect of the present disclosure, there is provided a method for predicting the gradation of recycled particles, including: inputting condition parameters into a milling particle gradation prediction model, wherein the milling particle gradation prediction model is obtained by the method as described above; and using the milling particle gradation prediction model and according to the condition parameters, calculating the proportion of the residue mass corresponding to each sieve.

[0017] In some embodiments, the condition parameters include: the rotational speed of the milling rotor and the forward speed of the milling rotor.

[0018] In some embodiments, the condition parameters further include the milling depth.

[0019] According to another aspect of the present disclosure, there is provided an apparatus for obtaining a milling particle gradation prediction model, including: a milling test unit configured to screen a plurality of sets of test particles obtained through a milling test after performing milling tests on an asphalt layer respectively using a plurality of sets of set test conditions, so as to obtain the proportion of the remaining mass corresponding to each of a plurality of sieves, wherein each set of the plurality of sets of test conditions includes: the rotational speed, the forward speed, and the milling depth of a milling rotor of an in-situ cold recycling device, and the plurality of sieves have different aperture specifications; a calculation unit configured to calculate characteristic parameters of a cutting diagram of the milling rotor according to the tooth arrangement mode of the cutter teeth of the milling rotor, the rotational speed, the forward speed, and the milling depth; a regression analysis unit configured to establish a functional relationship between the proportion of the remaining mass corresponding to each of the sieves obtained through the milling test and the characteristic parameters of the cutting diagram of the milling rotor through regression analysis according to the rotational speed, the forward speed, and the milling depth, wherein the proportion of the remaining mass corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor; and a normalization unit configured to perform normalization processing on the functional relationship to obtain a milling particle gradation prediction model.

[0020] According to another aspect of the present disclosure, there is provided an apparatus for obtaining a milling particle gradation prediction model, including: a memory; and a processor coupled to the memory, the processor being configured to execute the method as described above based on instructions stored in the memory.

[0021] According to another aspect of the present disclosure, there is provided a prediction apparatus for recycled particle gradation, including: an input module configured to input condition parameters into a milling particle gradation prediction model, wherein the milling particle gradation prediction model is obtained through the method according to any one of claims 1 to 9; and a calculation module configured to use the milling particle gradation prediction model and calculate the proportion of the remaining mass corresponding to each sieve according to the condition parameters.

[0022] According to another aspect of the present disclosure, there is provided a prediction apparatus for recycled particle gradation, including: a memory; and a processor coupled to the memory, the processor being configured to execute the method as described above based on instructions stored in the memory.

[0023] According to another aspect of the present disclosure, there is provided a milling rotor for an in-situ cold recycling device, comprising: a drum; and multiple rows of cutter teeth spirally arranged on the drum, wherein the multiple rows of cutter teeth include a plurality of cutter tooth groups arranged along the axial direction of the drum; wherein each cutter tooth group includes a first cutter tooth, a second cutter tooth, and a third cutter tooth, the first cutter tooth, the second cutter tooth, and the third cutter tooth are respectively located in different rows of the multiple rows of cutter teeth, a projection of the second cutter tooth on the axis of the drum is located between a projection of the first cutter tooth on the axis of the drum and a projection of the third cutter tooth on the axis of the drum, and a difference between a circumferential angle of the third cutter tooth and a circumferential angle of the first cutter tooth is less than a difference between a circumferential angle of the second cutter tooth and a circumferential angle of the first cutter tooth.

[0024] In some embodiments, during the process of milling an asphalt layer using the milling rotor, the asphalt layer is cut in the order of the first cutter tooth, the third cutter tooth, and the second cutter tooth.

[0025] In some embodiments, in the axial direction of the drum, the distance between adjacent cutter teeth ranges from 16 mm to 22 mm.

[0026] According to another aspect of the present disclosure, there is provided an in-situ cold recycling device, comprising: the prediction device for regenerated particle gradation as described above; and / or the milling rotor for an in-situ cold recycling device as described above.

[0027] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer program instructions, which when executed by a processor implement the method as described above.

[0028] In the above method, by obtaining the milling particle gradation prediction model, it is convenient to predict the particle gradation of the pavement recycled material under different construction parameters, thereby solving as much as possible the problem in the in-situ cold recycling construction of the asphalt layer in the related art that it is necessary to repeatedly conduct road section tests to determine the operation parameters, saving a large amount of manpower and material resources, and shortening the construction time.

[0029] Other features and advantages of the present disclosure will become clear through the following detailed description of the exemplary embodiments of the present disclosure with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings forming a part of the specification depict embodiments of the present disclosure and, together with the description, are used to explain the principles of the present disclosure.

[0031] Referring to the accompanying drawings, the present disclosure can be more clearly understood from the following detailed description, wherein:

[0032] Figure 1is a three-dimensional structural schematic diagram showing a milling rotor for an in-situ cold recycling device according to an embodiment of the present disclosure;

[0033] Figure 2 is a developed schematic diagram showing the arrangement of cutter teeth of a milling rotor for an in-situ cold recycling device according to an embodiment of the present disclosure;

[0034] Figure 3 is a schematic diagram showing the circumferential angle of cutter teeth of a milling rotor according to some embodiments of the present disclosure;

[0035] Figure 4 is a flowchart showing a method for obtaining a milling particle gradation prediction model according to an embodiment of the present disclosure;

[0036] Figure 5 is a cutting diagram schematically showing the cutter teeth of a milling rotor according to an embodiment of the present disclosure;

[0037] Figure 6 is a milling diagram showing the cutter teeth of a milling rotor according to an embodiment of the present disclosure;

[0038] Figure 7 is a schematic diagram showing a cutting unit pattern according to an embodiment of the present disclosure;

[0039] Figure 8 is a flowchart showing a prediction method for recycled particle gradation according to an embodiment of the present disclosure;

[0040] Figure 9 is a structural block diagram showing a device for obtaining a milling particle gradation prediction model according to an embodiment of the present disclosure;

[0041] Figure 10 is a structural block diagram showing a device for obtaining a milling particle gradation prediction model according to another embodiment of the present disclosure;

[0042] Figure 11 is a structural block diagram showing a device for obtaining a milling particle gradation prediction model according to another embodiment of the present disclosure;

[0043] Figure 12 is a structural block diagram showing a prediction device for recycled particle gradation according to an embodiment of the present disclosure;

[0044] Figure 13 is a structural block diagram showing a prediction device for recycled particle gradation according to another embodiment of the present disclosure. Detailed implementation manners

[0045] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure.

[0046] Meanwhile, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationship.

[0047] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way a limitation on the present disclosure or its application or use.

[0048] Technologies, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the said technologies, methods and devices should be regarded as part of the specification.

[0049] In all the examples shown and discussed herein, any specific values should be construed as merely exemplary and not as a limitation. Thus, other examples of the exemplary embodiments may have different values.

[0050] It should be noted that: like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0051] Figure 1 is a schematic perspective view showing the three-dimensional structure of a milling rotor for an in-situ cold recycling device according to an embodiment of the present disclosure. As Figure 1 shown, the milling rotor 10 includes a drum 110 and multiple rows of cutter teeth 120 spirally arranged on the drum 110. For example, the drum is a cylindrical drum. Figure 1 The circumferential direction of the drum (i.e., the circumferential direction of the milling rotor) 131 and the axial direction of the drum (i.e., the axial direction of the milling rotor) 132 are also shown. For example, the above-mentioned milling rotor can be used for the implementation of in-situ cold recycling of an asphalt layer (e.g., an asphalt surface course).

[0052] Figure 2 is an unfolded schematic view showing the arrangement of the cutter teeth of the milling rotor for the in-situ cold recycling device according to an embodiment of the present disclosure. The Figure 2 is the Figure 1 layout diagram of the cutter teeth obtained by unfolding the perspective view along the circumferential direction 131 of the drum. Additionally, Figure 2 the circumferential angle C x of the cutter teeth is also shown, and the range of this C x is from 0° to 360°.

[0053] Figure 2, multiple rows of cutter teeth are shown, for example, the first row of cutter teeth to the sixth row of cutter teeth, etc. Each row of cutter teeth has a plurality of cutter teeth. Figure 2 The blade teeth i are shown as an example 1 、i 2 、i 3 、i 4 、i 5 、i 6 ……i x ……(Right now Figure 1 The plurality of rows of teeth include a plurality of tooth groups, which are arranged along the axis direction 132 of the drum. 1 、i 2 and i 3 The first tooth group is composed of tooth i 4 、i 5 and i 6 The second blade tooth group is formed, and so on. The first blade tooth group and the second blade tooth group are arranged along the axial direction 132 of the drum.

[0054] like Figure 2 As shown, each blade tooth group includes a first blade tooth, a second blade tooth and a third blade tooth. Taking the first blade tooth group as an example, the first blade tooth group includes a first blade tooth i 1 , second tooth i 2 and the third tooth i 3 The first blade tooth, the second blade tooth and the third blade tooth are respectively located in different rows of the plurality of blade teeth. 1 Located in row III, second tooth i 2 Located in row I, third tooth i 3 Located in row V.

[0055] The projection of the second tooth on the axis of the drum is between the projection of the first tooth on the axis of the drum and the projection of the third tooth on the axis of the drum. 2 The projection on the axis 132 of the drum 110 is located at the first tooth i 1 The projection on the axis 132 of the drum 110 and the third tooth i 3 Between the projections onto the axis 132 of the drum 110 .

[0056] Figure 3 is a schematic diagram showing the circumferential angle of the cutter teeth of a milling rotor according to some embodiments of the present disclosure.

[0057] The blade teeth are positioned on the drum by the circumferential angle and the axial position. The circumferential angle of the blade teeth is the angle of the blade teeth in the circumferential direction of the rotor drum. For example, if the circumferential angle is set to 0°, a blade tooth i xThe radian between the projection on the circular bottom surface of the cylindrical drum and the projection of the 0° position on the circular bottom surface is the circumferential angle C of the cutter tooth i x of the cutter tooth i x . For example, Figure 3 shows the circumferential angle C of the cutter tooth i 1 of the cutter tooth i 1 , the circumferential angle C of the cutter tooth i 2 of the cutter tooth i 2 and the circumferential angle C of the cutter tooth i 3 of the cutter tooth i 3 .

[0058] In the embodiments of the present disclosure, in each cutter tooth group, the difference between the circumferential angle of the third cutter tooth and the circumferential angle of the first cutter tooth is less than the difference between the circumferential angle of the second cutter tooth and the circumferential angle of the first cutter tooth. For example, as Figure 3 shown, the difference between the circumferential angle C 3 of the third cutter tooth i 3 and the circumferential angle C 1 of the first cutter tooth i 1 (i.e., C 3 - C 1 ) is less than the difference between the circumferential angle C 2 of the second cutter tooth i 2 and the circumferential angle C 1 of the first cutter tooth i 1 (i.e., C 2 - C 1 ).

[0059] So far, a milling rotor for an in-situ cold recycling device according to some embodiments of the present disclosure has been provided. The milling rotor includes: a drum; and multiple rows of cutter teeth spirally arranged on the drum, wherein the multiple rows of cutter teeth include multiple cutter tooth groups, and the multiple cutter tooth groups are arranged along the axial direction of the drum; wherein each cutter tooth group includes a first cutter tooth, a second cutter tooth, and a third cutter tooth, the first cutter tooth, the second cutter tooth, and the third cutter tooth are respectively located in different rows of the multiple rows of cutter teeth, the projection of the second cutter tooth on the axis of the drum is located between the projection of the first cutter tooth on the axis of the drum and the projection of the third cutter tooth on the axis of the drum, and the difference between the circumferential angle of the third cutter tooth and the circumferential angle of the first cutter tooth is less than the difference between the circumferential angle of the second cutter tooth and the circumferential angle of the first cutter tooth. Using such a milling rotor can obtain relatively uniform and square particles when milling an asphalt layer (for example, an asphalt surface layer), which is beneficial to the implementation of the in-situ cold recycling process.

[0060] During the process of milling an asphalt layer (for example, an asphalt surface layer) using the above milling rotor, the asphalt layer can be cut into in the order of the first cutter tooth, the third cutter tooth, and the second cutter tooth.

[0061] In the above-mentioned arrangement of the teeth of the milling rotor, the adjacent teeth in the axial direction of the milling rotor are arranged in a "jumping" feed. 1 、Knife teeth 2 and blade teeth 3 ) is the cutter tooth group for analysis, cutter tooth i 1 First cut into the road surface, then with the blade teeth i 1 One busbar apart (i.e. Figure 2 The dotted line perpendicular to the axis direction) 210 of the blade i 3 Cut into the road surface, then with the blade teeth i 1 Adjacent teeth i 2 Cut into the road surface; blade teeth 4 、Knife teeth 5 、Knife teeth 6 The other teeth on the milling rotor also adopt this "jumping" feed arrangement.

[0062] In some embodiments, Figure 2 As shown, in the axial direction of the drum, the distance T between adjacent teeth ranges from 16 mm to 22 mm. 1 With blade teeth 2 The distance T between them is 16 mm to 22 mm. This distance design is combined with the "jumping" arrangement of the cutter teeth. Under the surface layer regeneration working condition (for example, the milling depth is 10 cm (centimeter) to 20 cm, and the forward speed is 3 m / min (meter / minute) to 6 m / min), the cutting pattern of the cutter teeth is close to square, which is conducive to obtaining uniformly shaped particles and a wider range of graded mixtures, thereby helping to meet the requirements of in-situ cold regeneration of the asphalt layer.

[0063] In some embodiments, Figure 1 As shown, multiple rows of cutter teeth are spirally arranged toward the middle of the rotor. During asphalt pavement milling operations, it is generally necessary to collect and transport the milling particles. The cutter teeth are wound toward the middle (i.e., spirally arranged), which can gather the milling particles toward the middle. A throwing port is arranged at a position corresponding to the middle position of the milling machine and the rotor, which makes it convenient to throw and transport the particles.

[0064] Figure 4 FIG. 1 is a flow chart showing a method for obtaining a milling particle gradation prediction model according to an embodiment of the present disclosure. Figure 4 As shown, the method includes steps S402 to S408.

[0065] In step S402, after milling tests are respectively carried out on the asphalt layer under multiple sets of set test conditions, the multiple sets of test particles obtained from the milling tests are screened to obtain the percentage of the residue mass corresponding to each of multiple sieves, where each set of test conditions in the multiple sets of test conditions includes: the rotation speed, the forward speed, and the milling depth of the milling rotor of the in-situ cold recycling equipment, and the multiple sieves have different aperture specifications (or called particle size specifications). For example, the asphalt layer is an asphalt surface layer.

[0066] Here, based on different level values of factors such as the tooth arrangement of the milling rotor, the set rotation speed of the milling rotor, the forward speed, and the milling depth, a three-factor multi-level orthogonal milling test on the asphalt layer can be carried out, the milling test particles are collected, the test particles of each group are screened, the percentage of the residue mass corresponding to each sieve (that is, the percentage of the mass of particles of corresponding various specifications) is calculated and analyzed, and the gradation of the recycled particles under different combinations of operating parameters is obtained.

[0067] In some embodiments, the percentage of the residue mass is the percentage of the cumulative residue. The percentage of the cumulative residue refers to the percentage of the residue mass on a certain sieve in the total mass of the sample.

[0068] Table 1 is an exemplary milling test table for the asphalt pavement surface layer. In this Table 1, there are a total of 5 sets of test conditions from 1# to 5#. In each set of test conditions, the rotation speed of the milling rotor, the forward speed, and the milling depth are set.

[0069] Table 1 Milling Test Table for Asphalt Pavement Surface Layer

[0070]

[0071] Table 2 is an exemplary particle screening test table. In this Table 2, sieves with 7 apertures are shown, and each sieve filters test particles of a corresponding size.

[0072] Table 2 Particle Screening Test Table

[0073]

[0074] For example, under the 1# test condition (the milling depth is 100 mm, the rotation speed of the milling rotor is 80 r / min (revolutions per minute), and the forward speed is 3 m / min), the test particles obtained are screened, and the percentages of the residue mass in Table 2 are respectively: the percentage of the residue mass of the sieve with an aperture of 19 mm is 6%, the percentage of the residue mass of the sieve with an aperture of 16 mm is 6%, the percentage of the residue mass of the sieve with an aperture of 13.2 mm is 9%, the percentage of the residue mass of the sieve with an aperture of 9.5 mm is 20%, the percentage of the residue mass of the sieve with an aperture of 4.75 mm is 30%, the percentage of the residue mass of the sieve with an aperture of 1.18 mm is 25%, and the percentage of the residue mass of the sieve with an aperture less than 1.18 mm is 4%.

[0075] It should be noted that the data in Table 1 and Table 2 above are all exemplary, and the scope of the present disclosure is not limited thereto.

[0076] In step S404, according to the tooth arrangement, rotational speed, forward speed, and milling depth of the milling rotor, characteristic parameters of the cutting diagram of the milling rotor are calculated.

[0077] Here, the cutting diagram is a diagram theoretically assumed to be drawn when the milling rotor rotates more than one week, and the cutting diagram reflects the traces left on the plane where the maximum milling thickness is located when the milling rotor passes through the maximum milling thickness.

[0078] Figure 5 is a schematic diagram showing the cutting diagram of the cutter teeth of the milling rotor according to an embodiment of the present disclosure. As Figure 5 shown, this cutting diagram shows the positions of cutter teeth i x-1 , i x and i x+1 etc. Here, x is a positive integer and x>1. Taking the xth cutter tooth i x as an example, the position of the cutter tooth on the cutting diagram can be expressed as coordinates (L x , P x ). Figure 5 also shows the chipping angle α corresponding to each cutter tooth. Here, it is assumed that the chipping angles corresponding to all cutter teeth are basically equal, all being α. On both sides of each cutter tooth position, a first chipping line 511 and a second chipping line 512 are respectively formed. For example, as Figure 5 shown, the first chipping line 511 is located on the left side of the cutter tooth position (the first chipping line can also be called the left chipping line), and the second chipping line 512 is located on the right side of the cutter tooth position (the second chipping line can also be called the right chipping line). In addition, Figure 5 also shows the maximum milling thickness h m . Figure 5 also shows the largest square 520 that can be formed in the cutting diagram, and this square 520 generally represents the shape of the particles formed during the milling process.

[0079] In some embodiments, this step S404 includes: according to the tooth arrangement, rotational speed, forward speed, and milling depth of the milling rotor, calculating the position when the xth cutter tooth i x of the milling rotor passes through the maximum milling thickness, where x is a positive integer and x>1.

[0080] As described above, the position when the xth cutter tooth of the milling rotor passes through the maximum milling thickness is the coordinates (L x , P z ). Here, L x is the abscissa of the xth cutter tooth in the direction parallel to the axis of the milling rotor in the cutting diagram, Lx is a known quantity; P x is the ordinate of the x-th cutting tooth in the direction perpendicular to the axis of the milling rotor in the cutting diagram.

[0081] For example,

[0082] wherein,

[0083] wherein, C x is the circumferential angle of the x-th cutting tooth, v is the forward speed of the milling rotor, n is the rotational speed of the milling rotor, H is the milling depth, R is the milling radius of the milling rotor, m is the number of complete rotations that the x-th cutting tooth has made, m≥0 and m is an integer. Here, C x , v, n, H, R, and m are all known quantities.

[0084] Figure 6 is a milling schematic diagram showing the cutting teeth of a milling rotor according to an embodiment of the present disclosure. The origin of the above formula (1) will be described in detail below in conjunction with Figure 5 and Figure 6 the above formula (1).

[0085] Since the milling rotor rotates and moves forward simultaneously during operation, the milling rotor cuts off the asphalt material during one rotation, and the amount of milling depth is in a state of being small first and then large. The milling depth when the milling rotor passes through the maximum position is the maximum milling thickness. As Figure 6 shown, the milling rotor first rotates through the rotation trajectory line 601, and then rotates through the next rotation trajectory line 602 during the forward movement.

[0086] In Figure 6 , S 1 represents the distance that the milling rotor moves forward in one rotation, then there is

[0087] In Figure 6 , the maximum milling thickness h m is

[0088]

[0089] wherein,

[0090] In the case where the milling rotor rotates one week, the angle that the cutting tooth i x rotates is C x , therefore, in the cutting diagram, the rotational length of the cutting tooth i x in the circumferential direction is

[0091]

[0092] During the rotation of the actual milling rotor, the rotor may rotate for multiple revolutions. Correspondingly, the cutter tooth i x rotates revolutions. Therefore, the ordinate P x of the x-th cutter tooth i x is

[0093]

[0094] In this way, the above formula (1) is obtained, and then the coordinates (L x , P x , P z ) of the cutter tooth i on the cutting diagram are obtained.

[0095] In some embodiments, the above step S404 further includes: calculating the equation expression of the caving line corresponding to the x-th cutter tooth according to the position of the x-th cutter tooth of the milling rotor when passing through the maximum milling thickness and the caving angle when the x-th cutter tooth mills the asphalt layer (for example, the asphalt surface course), so as to obtain the equation expressions of the caving lines corresponding to multiple cutter teeth of the milling rotor, and the multiple cutter teeth include the x-th cutter tooth.

[0096] For example, as Figure 5 shown, the slope of the caving line in the cutting diagram can be calculated based on the caving angle. The slope of the first caving line 511 corresponding to the cutter tooth i x is tan The slope of the second caving line 512 corresponding to the cutter tooth i x is tan According to the coordinates (L x , P x , P x ) of the cutter tooth i on the cutting diagram calculated previously and the slope of the first caving line 511, the equation expression of the first caving line 511 corresponding to the x-th cutter tooth i x can be obtained; according to the coordinates (L x , P x , P x ) of the cutter tooth i on the cutting diagram and the slope of the second caving line 512, the equation expression of the second caving line 512 corresponding to the x-th cutter tooth i x can be obtained.

[0097] In addition, through a calculation process similar to the above calculation process, the equation expressions of the caving lines corresponding to other cutter teeth can also be obtained. For example, the equation expressions of the caving lines of the cutter teeth i x-1 , i x+1 , i x+2 , etc.

[0098] In some embodiments, the above step S404 further includes: calculating, according to the equation expressions of the spalling lines corresponding to the multiple cutter teeth of the milling rotor and the cutting diagram of the milling rotor, the characteristic parameters of the cutting unit pattern corresponding to the x-th cutter tooth, as the characteristic parameters of the cutting diagram of the milling rotor.

[0099] In some embodiments, calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th cutter tooth according to the equation expressions of the spalling lines corresponding to the multiple cutter teeth of the milling rotor and the cutting diagram of the milling rotor includes: obtaining the equation expressions of the multiple sides of the cutting unit pattern corresponding to the x-th cutter tooth according to the equation expressions of the spalling lines corresponding to the multiple cutter teeth of the milling rotor; calculating the position coordinates of the multiple vertices of the cutting unit pattern corresponding to the x-th cutter tooth according to the equation expressions of the multiple sides of the cutting unit pattern corresponding to the x-th cutter tooth; and calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th cutter tooth according to the position coordinates of the multiple vertices.

[0100] For example, Figure 7 is a schematic diagram showing a cutting unit pattern according to an embodiment of the present disclosure. As Figure 7 shown, the cutting unit pattern of the cutter tooth i x is formed by line segments i x J 13 , i x J 23 , J 13 J 01 , i x+1 J 01 , i x+1 J 02 and J 23 J 02 enclosed. These line segments are respectively the sides of the cutting unit pattern. Here, the straight line where each line segment is located is the equation expression of the spalling line corresponding to the corresponding cutter tooth. For example, the straight line where the line segment i x J 13 is located is the equation expression of the first spalling line corresponding to the cutter tooth i x , the straight line where the line segment i x J 23 is located is the equation expression of the second spalling line corresponding to the cutter tooth i x , the straight line where the line segment J 23 J 02 is located is the equation expression of the first spalling line of the cutter tooth i x-1 (which can be seen in combination with Figure 5 ), the straight line where the line segment i x+1 J 02 is located is the equation expression of the second spalling line of the cutter tooth i x+1 , the straight line where the line segment i x+1 J 01 is located is the equation expression of the cutter tooth ix+1 The equation expression of the first caving line, and the line segment J 13 J 01 The line where it is located is the equation expression of the second caving line of another cutter tooth (for example, it can be called cutter tooth i x+2 ). It can be seen in combination with Figure 5 ). In this way, the equation expressions of the multiple sides of the cutting unit pattern corresponding to the x-th cutter tooth are obtained according to the equation expressions of the caving lines corresponding to the multiple cutter teeth of the milling rotor.

[0101] As Figure 7 shown, each vertex of the cutting unit pattern is the intersection of the corresponding two sides. For example, vertex J 23 is the intersection of side i x J 23 and J 23 J 02 , vertex J 02 is the intersection of side i x+1 J 02 and J 23 J 02 , and so on. Since two intersecting lines can determine an intersection point, the position coordinates of the corresponding vertex can be calculated according to the equation expressions of the two intersecting sides. For example, according to the equation expressions of side i x J 23 and J 23 J 02 obtained previously, the coordinates of vertex J 23 can be calculated. According to the equation expressions of side i x+1 J 02 and J 23 J 02 obtained previously, the coordinates of vertex J 02 can be calculated. The coordinates of other vertices can also be obtained in this way, which will not be elaborated here one by one. Therefore, the position coordinates of the multiple vertices of the cutting unit pattern corresponding to the x-th cutter tooth can be calculated according to the equation expressions of the multiple sides of the cutting unit pattern corresponding to the x-th cutter tooth.

[0102] Next, the characteristic parameters of the cutting unit pattern corresponding to the x-th cutter tooth are calculated according to the position coordinates of the multiple vertices.

[0103] In some embodiments, the characteristic parameter of the cutting unit pattern corresponding to the x-th cutter tooth is: the length of the hypotenuse of a right triangle constructed with one side of the cutting unit pattern as a right-angled side and according to a predetermined composition method inside the cutting unit pattern.

[0104] For example, as Figure 7 shown, with the side J 23 J02 As the first right-angled side, with respect to the first right-angled side J 23 J 02 Construct a perpendicular line MJ perpendicular to it 23 As the second right-angled side, and with this perpendicular line MJ 23 In the cutting unit pattern, with respect to the first right-angled side J 23 J 02 Of the opposite side i x J 13 Construct a right triangle MJ with the intersection point M between them as a vertex 23 J 02 That is, the right triangle MJ 23 J 02 The length of the hypotenuse MJ 02 Of which is the characteristic parameter of the cutting unit pattern corresponding to the x-th cutting tooth. Here, inside the cutting unit pattern, taking one side of the cutting unit pattern as a right-angled side and constructing a right triangle according to a predetermined composition method, the length of the hypotenuse of this right triangle is the characteristic parameter of the cutting unit pattern.

[0105] Since the position coordinates of multiple vertices of the cutting unit pattern have been calculated previously, the length of the hypotenuse of the above right triangle can be calculated based on the position coordinates of these multiple vertices, that is, the characteristic parameter of the cutting unit pattern corresponding to the x-th cutting tooth is obtained.

[0106] Of course, those skilled in the art can understand that the characteristic parameters of the above cutting unit pattern are only exemplary, and the scope of the present disclosure is not limited thereto. For example, other sides of the cutting unit pattern can be used as a right-angled side to construct a right triangle inside the cutting unit pattern, and the length of the hypotenuse of this right triangle is the characteristic parameter of the cutting unit pattern.

[0107] In some other embodiments, other structural features of the cutting unit pattern can also be used as the characteristic parameters of the cutting unit pattern. For example, the area of the cutting unit pattern can be used as the characteristic parameter of the cutting unit pattern, or the area of a certain shape (such as a triangle) constructed inside the cutting unit pattern can be used as the characteristic parameter of the cutting unit pattern, and so on. Details are not elaborated here one by one.

[0108] Since the position coordinates of multiple vertices of the cutting unit pattern have been calculated previously, the characteristic parameters of the above cutting unit pattern can be calculated based on the position coordinates of these multiple vertices. For example, the length of the hypotenuse of other constructed right triangles, the area of the cutting unit pattern and other characteristic parameters.

[0109] In this way, in the above steps, the positions of the cutter teeth are calculated, and then in combination with the spalling angle α of the asphalt pavement, the spalling line corresponding to the x-th cutter tooth is calculated, the calculation framework of the cutting diagram of the milling rotor is built, the algorithm program for drawing the cutting diagram is written, the cutting diagram of the rotor is drawn under the same combination of test parameters as the milling test of the asphalt pavement surface layer, and the characteristic parameters of the cutting diagram of the milling rotor are calculated.

[0110] In step S406, according to the rotational speed, the forward speed, and the milling depth, through regression analysis, a functional relationship is established between the proportion of the residue mass corresponding to each sieve obtained through the milling test and the characteristic parameters of the cutting diagram of the milling rotor, where the proportion of the residue mass corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor.

[0111] In this step, based on parameters such as the milling depth, the rotor rotational speed, and the forward speed, the milling test data (i.e., the proportion of the residue mass corresponding to each sieve in step S402) and the characteristic parameters of the cutting diagram of the milling rotor (i.e., the characteristic parameters in step S404) (as shown in Table 3, for example) are integrated, and through regression analysis, a functional relationship, that is, a mathematical relationship, between the two is established.

[0112] If the milling test is carried out according to the 5 groups of test condition parameters in Table 1, then when calculating the characteristic parameters of the cutting diagram, it is also calculated according to these 5 groups of test condition parameters, that is, the corresponding characteristic parameters of the cutting diagram are calculated using the milling depth, the rotor rotational speed, and the forward speed of the corresponding group in Table 1. This ensures that the variables used in the milling test and the calculation of the characteristic parameters of the cutting diagram correspond one by one, facilitating the establishment of the milling particle size distribution prediction model.

[0113] Table 3 Example table for integrating milling test data and characteristic parameters of the cutting diagram

[0114]

[0115] In some embodiments, the functional relationship between the proportion of the residue mass corresponding to each sieve and the characteristic parameters of the cutting diagram of the milling rotor is

[0116]

[0117] where is the proportion of the residue mass of the -th sieve, τ is the characteristic parameter of the cutting diagram of the milling rotor, and are coefficients. The coefficients and can be determined according to multiple groups of test data (as shown in Table 3, for example).

[0118] For example, by integrating the corresponding data of the percentage of residue mass corresponding to each sieve and the characteristic parameters of the cutting diagram of the milling rotor (as shown in Table 3 for example), the functional relationship between the percentage of residue mass corresponding to each sieve and the characteristic parameters of the cutting diagram of the milling rotor can be obtained through polynomial fitting. The more data there are, the stronger the regularity and the more obvious the mathematical relationship.

[0119] In step S408, the functional relationship is normalized to obtain a milling particle size distribution prediction model.

[0120] In some embodiments, this step S408 includes: calculating the theoretical value of the percentage of residue mass corresponding to each sieve of multiple sieves according to the characteristic parameters of the cutting diagram of the milling rotor and the functional relationship; calculating the sum of the theoretical values of the percentage of residue mass corresponding to the multiple sieves; and normalizing the functional relationship by using the sum of the theoretical values of the percentage of residue mass corresponding to the multiple sieves.

[0121] Here, after establishing the above functional relationship through regression analysis, substituting the characteristic parameters of the cutting diagram of the milling rotor into the functional relationship to calculate the theoretical value of the percentage of residue mass corresponding to each sieve; calculating the sum of the theoretical values of the percentage of residue mass corresponding to all sieves, and this sum value may not be equal to 100%. In such a case, the functional relationship is normalized by using the above sum value. That is, dividing the polynomial of the functional relationship formula (5) by this sum value realizes the normalization of the functional relationship. For example, if the sum value is calculated to be 1.01, then dividing by 1.01 realizes the normalization of the functional relationship.

[0122] By normalizing all functional relationships, it can be ensured as much as possible that the sum of the percentage of residue mass corresponding to each aperture sieve is 100%, making the prediction of the milling particle size distribution prediction model more accurate.

[0123] So far, a method for obtaining a milling particle gradation prediction model according to some embodiments of the present disclosure is provided. The method includes: after performing a milling test on the asphalt layer respectively using multiple groups of test conditions set, screening multiple groups of test particles obtained by the milling test to obtain the sieve residue mass ratio corresponding to each of the multiple sieves, wherein each group of test conditions in the multiple groups of test conditions includes: the rotation speed, forward speed and milling depth of the milling rotor of the in-situ cold regeneration equipment, and the multiple sieves have different aperture specifications; according to the tooth arrangement mode, rotation speed, forward speed and milling depth of the milling rotor, the characteristic parameters of the cutting diagram of the milling rotor are calculated; according to the rotation speed, forward speed and milling depth, through regression analysis, a functional relationship between the sieve residue mass ratio corresponding to each sieve obtained by the milling test and the characteristic parameters of the cutting diagram of the milling rotor is established, wherein the sieve residue mass ratio corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor; and normalizing the functional relationship to obtain a milling particle gradation prediction model. By obtaining the milling particle gradation prediction model, it is easy to predict the particle gradation of road recycled materials under different construction parameters, thereby solving the problem that the operation parameters need to be determined by repeated road section tests in the in-situ cold recycling construction of the asphalt layer in the related technology, saving a lot of manpower and material resources and shortening the construction time. This method also prevents the waste of asphalt layer materials as much as possible.

[0124] In the above-mentioned embodiment of the present disclosure, by carrying out orthogonal tests on milling of multi-level asphalt layers (for example, asphalt surface layers) with three factors of milling depth, rotor speed and forward speed, a database of the relationship between operating parameter combinations and recycled particle grading is obtained, thereby avoiding on-site milling tests of pavement regeneration construction sites; combined with the cutting diagram calculation method, an asphalt layer milling particle grading prediction model is established to realize the prediction of pavement recycled material grading under different construction parameters, thus solving the problem that each pavement regeneration construction requires section tests to determine the operating parameters, saving a lot of manpower and material resources and shortening the construction period.

[0125] Figure 8 FIG. 1 is a flow chart showing a method for predicting the regeneration particle gradation according to an embodiment of the present disclosure. Figure 8 As shown, the prediction method includes steps S802 to S804.

[0126] In step S802, condition parameters are input into the milling particle gradation prediction model. The milling particle gradation prediction model is implemented by the method described above (e.g. Figure 4 obtained by the method shown).

[0127] In some embodiments, the conditional parameters include: the rotational speed of the milling rotor and the forward speed of the milling rotor. Here, when the milling depth is a constant (for example, the milling depth can be pre-set in the model), the conditional parameters input into the milling particle grading prediction model are the rotational speed of the milling rotor and the forward speed of the milling rotor. For example, the rotational speed of the milling rotor ranges from 80r / min to 120r / min. The rotational speed can be adjusted within this range. For example, the forward speed ranges from 3m / min to 6m / min. The forward speed can be adjusted within this range. Of course, the scope of the present disclosure is not limited to this.

[0128] In some embodiments, the conditional parameters also include milling depth. That is, when the milling depth is not a constant value, the conditional parameters include the rotation speed of the milling rotor, the forward speed of the milling rotor and the milling depth. These three conditional parameters are input into the milling particle gradation prediction model.

[0129] In step S804, the milling particle gradation prediction model is used and according to the condition parameters, the mass percentage of the residue corresponding to each sieve is calculated.

[0130] Here, after the condition parameters are input into the milling particle gradation prediction model, the milling particle gradation prediction model can calculate the characteristic parameters of the corresponding cutting diagram, and then calculate the screen residue mass proportion corresponding to each screen according to the functional relationship (5).

[0131] So far, a prediction method for recycled particle gradation according to some embodiments of the present disclosure is provided. The method comprises: inputting condition parameters into a milling particle gradation prediction model, wherein the milling particle gradation prediction model is obtained by the above method; and using the milling particle gradation prediction model and according to the condition parameters, calculating the mass proportion of the sieve residue corresponding to each sieve. The method realizes the prediction of the gradation of pavement recycled materials under different construction parameters, saves the manpower and material resources required in the related technology, and shortens the construction time. The method also prevents the waste of asphalt layer materials and other problems as much as possible.

[0132] For example, in the grading prediction of asphalt pavement in-situ cold recycling materials, for the specific asphalt pavement in-situ cold recycling construction project, the milling depth is generally determined by the specific pavement structure, the rotor speed and forward speed are adjustable, and different rotor speed and forward speed parameter combinations are set during the in-situ cold recycling construction, and the characteristic parameters of the cutting diagram under the corresponding operating parameter combination are calculated. The milling particle grading prediction model is used to analyze the mass proportion of the sieve residue of each specification number, complete the grading prediction of the recycled materials, and select the operating parameter combination that meets the construction grading requirements for the pavement in-situ cold recycling construction.

[0133] Figure 9is a structural block diagram showing an apparatus for obtaining a milling particle gradation prediction model according to an embodiment of the present disclosure.

[0134] like Figure 9 As shown, the device includes a milling test unit 902 , a calculation unit 904 , a regression analysis unit 906 and a normalization unit 908 .

[0135] The milling test unit 902 is configured to, after performing milling tests on the asphalt layer respectively using the set multiple groups of test conditions, screen the multiple groups of test particles obtained by the milling test to obtain the sieve residue mass percentage corresponding to each of the multiple sieves, wherein each group of test conditions in the multiple groups of test conditions includes: the rotation speed, forward speed and milling depth of the milling rotor of the in-situ cold regeneration equipment, and the multiple sieves have different aperture specifications.

[0136] The calculation unit 904 is configured to calculate characteristic parameters of the cutting diagram of the milling rotor according to the tooth arrangement, rotation speed, forward speed and milling depth of the milling rotor.

[0137] The regression analysis unit 906 is configured to establish a functional relationship between the percentage of the sieve residue mass corresponding to each sieve obtained through the milling test and the characteristic parameters of the cutting diagram of the milling rotor through regression analysis based on the rotational speed, forward speed and milling depth, wherein the percentage of the sieve residue mass corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor.

[0138] The normalization unit 908 is configured to perform normalization processing on the functional relationship to obtain a milling particle gradation prediction model.

[0139] Thus, a device for obtaining a milling particle gradation prediction model according to some embodiments of the present disclosure is provided. The device can facilitate the prediction of the particle gradation of road surface recycled materials under different construction parameters, thereby solving the problem that the operation parameters need to be determined by repeated road section tests in the in-situ cold regeneration construction of the asphalt layer in the related technology, saving a lot of manpower and material resources and shortening the construction time. The device also prevents the waste of asphalt layer materials as much as possible.

[0140] In some embodiments, the computing unit 904 is configured to calculate the position of the x-th cutting tooth of the milling rotor when passing through the maximum milling thickness according to the tooth arrangement, rotational speed, forward speed, and milling depth of the milling rotor, where x is a positive integer and x > 1; calculate the equation expression of the crumbling line corresponding to the x-th cutting tooth according to the position of the x-th cutting tooth of the milling rotor when passing through the maximum milling thickness and the crumbling angle when the x-th cutting tooth mills the asphalt layer, so as to obtain the equation expressions of the crumbling lines corresponding to multiple cutting teeth of the milling rotor, and the multiple cutting teeth include the x-th cutting tooth; and calculate the characteristic parameters of the cutting unit pattern corresponding to the x-th cutting tooth according to the equation expressions of the crumbling lines corresponding to multiple cutting teeth of the milling rotor and the cutting diagram of the milling rotor, as the characteristic parameters of the cutting diagram of the milling rotor.

[0141] In some embodiments, the position of the x-th cutting tooth of the milling rotor when passing through the maximum milling thickness is the coordinate (L x , P x ), where L x is the abscissa of the x-th cutting tooth in the direction parallel to the axis of the milling rotor in the cutting diagram, and L x is a known quantity; P x is the ordinate of the x-th cutting tooth in the direction perpendicular to the axis of the milling rotor in the cutting diagram. Where Where C x is the circumferential angle of the x-th cutting tooth, v is the forward speed of the milling rotor, n is the rotational speed of the milling rotor, H is the milling depth, R is the milling radius of the milling rotor, and m is the number of complete rotations that the x-th cutting tooth has rotated, m ≥ 0 and m is an integer.

[0142] In some embodiments, the computing unit 904 is configured to obtain the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th cutting tooth according to the equation expressions of the crumbling lines corresponding to multiple cutting teeth of the milling rotor; calculate the position coordinates of multiple vertices of the cutting unit pattern corresponding to the x-th cutting tooth according to the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th cutting tooth; and calculate the characteristic parameters of the cutting unit pattern corresponding to the x-th cutting tooth according to the position coordinates of multiple vertices.

[0143] In some embodiments, the characteristic parameter of the cutting unit pattern corresponding to the x-th cutting tooth is: the length of the hypotenuse of a right triangle constructed with one side of the cutting unit pattern as a right side inside the cutting unit pattern according to a predetermined composition method.

[0144] In some embodiments, the functional relationship between the proportion of the residue mass corresponding to each sieve and the characteristic parameters of the cutting diagram of the milling rotor is

[0145]

[0146] Among them, is the percentage by mass of the residue on the -mesh sieve, τ is a characteristic parameter of the cutting diagram of the milling rotor, and are coefficients.

[0147] In some embodiments, the normalization unit 908 is configured to calculate the theoretical value of the percentage by mass of the residue corresponding to each sieve of a plurality of sieves according to the characteristic parameter of the cutting diagram of the milling rotor and the functional relationship; calculate the sum of the theoretical values of the percentage by mass of the residue corresponding to the plurality of sieves according to the theoretical value of the percentage by mass of the residue corresponding to each sieve; and use the sum of the theoretical values of the percentage by mass of the residue corresponding to the plurality of sieves to perform normalization processing on the functional relationship.

[0148] The device for obtaining a milling particle size distribution prediction model provided by the embodiments of the present disclosure can execute the method for obtaining a milling particle size distribution prediction model provided by any embodiment of the present disclosure, and has the corresponding functional units and beneficial effects for executing the method.

[0149] Figure 10 FIG. is a structural block diagram of a device for obtaining a milling particle size distribution prediction model according to another embodiment of the present disclosure. The device includes a memory 1010 and a processor 1020.

[0150] Wherein:

[0151] The memory 1010 may be a magnetic disk, a flash memory, or any other non-volatile storage medium. The memory is used to store Figure 4 the instructions in the corresponding embodiment.

[0152] The processor 1020 is coupled to the memory 1010 and may be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 1020 is used to execute the instructions stored in the memory to realize the prediction of the particle size distribution of the pavement recycling material under different construction parameters and shorten the construction time.

[0153] In one embodiment, as shown in Figure 11 FIG., the device 1100 for obtaining a milling particle size distribution prediction model includes a memory 1110 and a processor 1120. The processor 1120 is coupled to the memory 1110 through a BUS bus 1130. The device 1100 may also be connected to an external storage device 1150 through a storage interface 1140 to call external data, and may also be connected to a network or another computer system (not shown) through a network interface 1160. Details are not described herein again.

[0154] In this embodiment, the memory stores data instructions, and the processor processes the instructions to achieve the prediction of the particle gradation of the road surface recycled material under different construction parameters, thereby shortening the construction time.

[0155] Figure 12 FIG. 1 is a block diagram showing a device for predicting regeneration particle gradation according to an embodiment of the present disclosure. Figure 12 As shown, the prediction device includes an input module 1210 and a calculation module 1220 .

[0156] The input module 1210 is configured to input condition parameters into the milling particle gradation prediction model. The milling particle gradation prediction model is obtained by the method described above.

[0157] In some embodiments, the condition parameters include: a rotational speed of the milling rotor and a forward speed of the milling rotor.

[0158] In some embodiments, the condition parameter further includes a milling depth.

[0159] The calculation module 1220 is configured to calculate the mass ratio of the residue corresponding to each sieve by using the milling particle gradation prediction model and according to the condition parameters.

[0160] Thus, a prediction device for regenerated particle gradation according to some embodiments of the present disclosure is provided. The prediction device realizes the prediction of the gradation of road surface recycled materials under different construction parameters, saves the manpower and material resources required in the related technology, and shortens the construction time. The device also prevents the waste of asphalt layer materials as much as possible.

[0161] The prediction device for regenerated particle grading provided in the embodiments of the present disclosure can execute the prediction method for regenerated particle grading provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0162] Figure 13 13 is a block diagram showing a prediction device for regeneration particle gradation according to another embodiment of the present disclosure. The prediction device includes a memory 1310 and a processor 1320. Wherein:

[0163] The memory 1310 may be a disk, a flash memory, or any other non-volatile storage medium. The memory is used to store Figure 8 The instructions in the corresponding embodiment.

[0164] The processor 1320 is coupled to the memory 1310 and can be implemented as one or more integrated circuits, such as a microprocessor or a microcontroller. The processor 1320 is used to execute instructions stored in the memory, and realizes the prediction of the gradation of road surface recycled materials under different construction parameters, thereby shortening the construction time.

[0165] In some embodiments of the present disclosure, an in-situ cold recycling device is further provided. The in-situ cold recycling device includes: the prediction device for regenerated particle gradation as described above; and / or the milling rotor for the in-situ cold recycling device as described above.

[0166] In some embodiments, the present disclosure also provides a non-transitory computer-readable storage medium, on which computer program instructions are stored, and when the instructions are executed by a processor, they implement Figure 4 and / or Figure 8 the steps of the methods in the corresponding embodiments. Those skilled in the art should understand that the embodiments of the present disclosure can be provided as methods, devices, or computer program products. Therefore, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable non-transitory storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0167] The present disclosure is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0168] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1Steps of the functions specified in one or more boxes.

[0170] So far, the present disclosure has been described in detail. To avoid obscuring the concept of the present disclosure, some details well known in the art have not been described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein based on the above description.

[0171] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art should understand that the above examples are only for illustration and not for limiting the scope of the present disclosure. Those skilled in the art should understand that the above embodiments can be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for obtaining a prediction model of milling particle gradation, comprising: After milling tests are respectively carried out on the asphalt layer under multiple sets of test conditions set, screening the multiple sets of test particles obtained from the milling tests to obtain the proportion of the remaining mass corresponding to each sieve among multiple sieves, wherein each set of test conditions among the multiple sets of test conditions includes: the rotational speed, the forward speed, and the milling depth of the milling rotor of the in-situ cold recycling equipment, and the multiple sieves have different aperture specifications; According to the tooth arrangement mode of the milling rotor, the rotational speed, the forward speed, and the milling depth, calculating the characteristic parameters of the cutting diagram of the milling rotor; According to the rotational speed, the forward speed, and the milling depth, through regression analysis, establishing a functional relationship between the proportion of the remaining mass corresponding to each sieve obtained from the milling test and the characteristic parameters of the cutting diagram of the milling rotor, wherein the proportion of the remaining mass corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor; and Normalizing the functional relationship to obtain a prediction model of milling particle gradation.

2. The method according to claim 1, wherein, Calculating the characteristic parameters of the cutting diagram of the milling rotor according to the tooth arrangement mode of the milling rotor, the rotational speed, the forward speed, and the milling depth includes: According to the tooth arrangement mode of the milling rotor, the rotational speed, the forward speed, and the milling depth, calculating the position when the x-th tooth of the milling rotor passes through the maximum milling thickness, where x is a positive integer and x > 1; According to the position when the x-th tooth of the milling rotor passes through the maximum milling thickness and the caving angle when the x-th tooth mills the asphalt layer, calculating the equation expression of the caving line corresponding to the x-th tooth, so as to obtain the equation expressions of the caving lines corresponding to multiple teeth of the milling rotor, and the multiple teeth include the x-th tooth; and According to the equation expressions of the caving lines corresponding to multiple teeth of the milling rotor and the cutting diagram of the milling rotor, calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th tooth as the characteristic parameters of the cutting diagram of the milling rotor.

3. The method according to claim 2, wherein, The position of the x-th cutting tooth of the milling rotor when passing through the maximum milling thickness is the coordinate ( , ). Among them, is the abscissa of the x-th cutting tooth in the direction parallel to the axis of the milling rotor in the cutting diagram, and the is a known quantity; is the ordinate of the x-th cutting tooth in the direction perpendicular to the axis of the milling rotor in the cutting diagram. , where , Among them, is the circumferential angle of the x-th cutting tooth, is the forward speed of the milling rotor, n is the rotational speed of the milling rotor, H is the milling depth, R is the milling radius of the milling rotor, m is the number of complete revolutions that the x-th cutting tooth has rotated, m≥0 and m is an integer.

4. The method according to claim 3, wherein, Calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th tooth according to the equation expressions of the caving lines corresponding to multiple teeth of the milling rotor and the cutting diagram of the milling rotor includes: Obtaining the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th tooth according to the equation expressions of the caving lines corresponding to multiple teeth of the milling rotor; Calculating the position coordinates of multiple vertices of the cutting unit pattern corresponding to the x-th tooth according to the equation expressions of multiple sides of the cutting unit pattern corresponding to the x-th tooth; and Calculating the characteristic parameters of the cutting unit pattern corresponding to the x-th tooth according to the position coordinates of the multiple vertices.

5. The method according to claim 4, wherein, The characteristic parameter of the cutting unit pattern corresponding to the x-th cutting tooth is: the length of the hypotenuse of a right triangle constructed with one side of the cutting unit pattern as a right side and according to a predetermined composition method inside the cutting unit pattern.

6. The method according to claim 1, wherein, the functional relationship between the proportion of the residue mass corresponding to each sieve and the characteristic parameter of the cutting pattern of the milling rotor is ， Among them, is the mass ratio of the residue on the φ-th sieve, and τ is the characteristic parameter of the cutting diagram of the milling rotor, , , and are coefficients.

7. The method according to claim 1, wherein, the normalization process of the functional relationship includes: calculating the theoretical value of the proportion of the residue mass corresponding to each sieve of multiple sieves according to the characteristic parameter of the cutting pattern of the milling rotor and the functional relationship; calculating the sum of the theoretical values of the proportion of the residue mass corresponding to the multiple sieves according to the theoretical value of the proportion of the residue mass corresponding to each sieve; and using the sum of the theoretical values of the proportion of the residue mass corresponding to the multiple sieves to normalize the functional relationship.

8. The method according to claim 1, wherein, the milling rotor includes: a drum; and multiple rows of cutting teeth spirally arranged on the drum, wherein the arrangement mode of the cutting teeth of the milling rotor is: the multiple rows of cutting teeth include multiple cutting tooth groups, and the multiple cutting tooth groups are arranged along the axial direction of the drum; wherein each cutting tooth group includes a first cutting tooth, a second cutting tooth and a third cutting tooth, the first cutting tooth, the second cutting tooth and the third cutting tooth are respectively located in different rows of the multiple rows of cutting teeth, the projection of the second cutting tooth on the axis of the drum is located between the projection of the first cutting tooth on the axis of the drum and the projection of the third cutting tooth on the axis of the drum, and the difference between the circumferential angle of the third cutting tooth and the circumferential angle of the first cutting tooth is less than the difference between the circumferential angle of the second cutting tooth and the circumferential angle of the first cutting tooth.

9. The method according to claim 8, wherein, during the process of milling the asphalt layer by using the milling rotor, the asphalt layer is cut in the order of the first cutting tooth, the third cutting tooth and the second cutting tooth.

10. A method for predicting the particle size distribution of recycled particles, including: inputting condition parameters into a milling particle size distribution prediction model, wherein the milling particle size distribution prediction model is obtained by the method according to any one of claims 1 to 9; and using the milling particle size distribution prediction model and according to the condition parameters, calculating the proportion of the residue mass corresponding to each sieve.

11. The prediction method according to claim 10, wherein, the condition parameters include: the rotation speed of the milling rotor and the forward speed of the milling rotor.

12. The prediction method according to claim 11, wherein, the condition parameters further include the milling depth.

13. An apparatus for obtaining a milling particle size distribution prediction model, including: A milling test unit, configured to screen multiple sets of test particles obtained through a milling test on an asphalt layer under multiple sets of set test conditions respectively, to obtain the proportion of the residual mass corresponding to each of multiple sieves, wherein each set of test conditions among the multiple sets of test conditions includes: the rotation speed, the forward speed, and the milling depth of the milling rotor of an in-situ cold recycling device, and the multiple sieves have different aperture specifications; A calculation unit, configured to calculate characteristic parameters of a cutting diagram of the milling rotor according to the tooth arrangement mode of the cutter teeth of the milling rotor, the rotation speed, the forward speed, and the milling depth; A regression analysis unit, configured to establish a functional relationship between the proportion of the residual mass corresponding to each sieve obtained through the milling test and the characteristic parameters of the cutting diagram of the milling rotor through regression analysis according to the rotation speed, the forward speed, and the milling depth, wherein the proportion of the residual mass corresponding to each sieve is a function of the characteristic parameters of the cutting diagram of the milling rotor; and A normalization unit, configured to perform normalization processing on the functional relationship to obtain a milling particle gradation prediction model.

14. An apparatus for obtaining a milling particle gradation prediction model, comprising: A memory; and A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 1 to 9 based on instructions stored in the memory.

15. A prediction apparatus for regenerated particle gradation, comprising: An input module, configured to input condition parameters to a milling particle gradation prediction model, wherein the milling particle gradation prediction model is obtained through the method according to any one of claims 1 to 9; and A calculation module, configured to calculate the proportion of the residual mass corresponding to each sieve by using the milling particle gradation prediction model and according to the condition parameters.

16. A prediction apparatus for regenerated particle gradation, comprising: A memory; and A processor coupled to the memory, the processor being configured to execute the method according to any one of claims 10 to 12 based on instructions stored in the memory.

17. A milling rotor for an in-situ cold recycling device applied to the method according to claim 1, comprising: A drum; and Multiple rows of cutter teeth spirally arranged on the drum, wherein the multiple rows of cutter teeth include multiple cutter tooth groups, and the multiple cutter tooth groups are arranged along the axial direction of the drum; wherein each cutter tooth group includes a first cutter tooth, a second cutter tooth, and a third cutter tooth, the first cutter tooth, the second cutter tooth, and the third cutter tooth are respectively located in different rows of the multiple rows of cutter teeth, the projection of the second cutter tooth on the axis of the drum is located between the projection of the first cutter tooth on the axis of the drum and the projection of the third cutter tooth on the axis of the drum, and the difference between the circumferential angle of the third cutter tooth and the circumferential angle of the first cutter tooth is less than the difference between the circumferential angle of the second cutter tooth and the circumferential angle of the first cutter tooth.

18. The milling rotor according to claim 17, wherein, During the process of milling the asphalt layer using the milling rotor, the asphalt layer is cut in the order of the first cutting tooth, the third cutting tooth, and the second cutting tooth.

19. The milling rotor according to claim 17, wherein in the axial direction of the drum, the distance between adjacent cutting teeth ranges from 16 mm to 22 mm.

20. An in-situ cold recycling device, comprising: a prediction device for regenerating particle gradation as described in claim 15 or 16; and / or a milling rotor for an in-situ cold recycling device as described in any one of claims 17 to 19.

21. A non-transitory computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the method as described in any one of claims 1 to 12 is implemented.

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