CN113386358B - Method and system for preparing standard artificial aggregate by additive technology - Google Patents
Method and system for preparing standard artificial aggregate by additive technology Download PDFInfo
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Abstract
The invention relates to a method and a system for preparing standard artificial aggregate by using an additive technology. The method for preparing the standard artificial aggregate by using the additive technology comprises the steps of determining the three-dimensional form of a natural aggregate according to an obtained evaluation index, obtaining a distribution rule of form parameters of the natural aggregate by adopting a statistical method based on the three-dimensional form of the natural aggregate, determining the standard form parameters of the aggregate based on the distribution rule, obtaining a standard model by reverse search and positioning based on the standard form parameters of the aggregate, and finally carrying out 3D printing on the natural aggregate based on the standard model to prepare the standard aggregate so as to solve the problems that the discreteness of a mixture test result generated by the morphological variation of the aggregate is overlarge, misleading effect is easily generated on the mix proportion design in engineering and the like, and further provide a direction for guiding the improvement of an aggregate processing technology.
Description
Technical Field
The invention relates to the technical field of aggregate preparation, in particular to a method and a system for preparing standard artificial aggregate by using an additive technology.
Background
For a long time, in order to improve various performances of asphalt mixtures, researches on aggregate characteristics have been conducted little starting from both the gradation composition of asphalt mixtures and asphalt raw materials. In the components of the asphalt mixture, the mass of the aggregate accounts for more than 90 percent of the total mass, and the specific gravity of the volume of the aggregate in the total volume of the mixture exceeds 75 percent. Therefore, the coarse aggregate plays a role in the weight of the asphalt pavement, and the embedding and extruding stability among the aggregates is one of important factors influencing the service performance and the durability of the asphalt pavement. In essence, the resource characteristics and the processing form of the aggregate have obvious influence on the high and low temperature performance, the anti-sliding function, the construction workability and other performances of the asphalt mixture.
At present, the mix proportion design and the mechanical property research of the asphalt mixture mostly adopt indoor tests, and because the form of the coarse aggregate is influenced by the characteristics of parent rock resources and the processing technology, even in the same stone yard, the processed coarse aggregate has the difference in form no matter the coarse aggregate is in grain form or edge angle form, and in addition, the operation and the system error in the test process cause that the test result has larger discreteness and can not truly reflect the form of the aggregate. The traditional test method cannot obtain mechanical test results under the same raw materials, different combinations, different environments and different load working conditions, so that the grading design work of the asphalt mixture cannot be accurately and visually carried out, and finally the optimization of the construction process cannot be guided.
The naturally processed coarse aggregate has various forms and single-specification gradation, and has square, round, flat, long and the like, so that the mix proportion test process of the asphalt mixture is caused, parallel group test data under the same gradation has variation fluctuation of up to 50%, and the difference of the test results of the mixture with different mineral aggregate gradations is influenced by errors in the group, so that the optimal mix proportion parameter of the asphalt mixture cannot be effectively determined.
The existing aggregate processing field has various management modes, different processing quality and variation of aggregates, including difference of particle morphology and difference of different particle size compositions of single-grade aggregates, so that in the engineering application process, even if the same production mixing ratio is used, different performances can be generated due to the change of aggregates processed by different stone fields. At present, when a stone yard changes, the mix proportion needs to be redesigned, one mix proportion needs about 1 month, the test cost is high, and high time and economic cost are brought to engineering projects.
In the process of carrying out asphalt mixture tests on natural aggregates, errors in groups fluctuate due to aggregate variation, and in order to obtain an error range specified by specifications, a large number of parallel tests are often required to be added, so that the workload and the test cost of a laboratory are increased.
The definition of the standard aggregate is not clear at present, and how to select aggregate particles as a standard model is the first premise for realizing the manufacture of a standard asphalt mixture test piece.
Conventionally, projection contour indexes of aggregates in X, Y and Z directions are generally calculated by adopting a digital image method, the difference between the perimeter and the projection area of the aggregate contour under different viewing angles is large, the intra-group range of extreme difference even reaches the intra-group mean value, and the three-dimensional morphological characteristics of the aggregates are difficult to represent by a single aggregate projection two-dimensional geometric index.
For the reasons, the prior art cannot realize standardization of coarse aggregate raw materials with different forms and eliminate errors generated by the forms of the raw materials, so that the problems that the discreteness of a mixture test result generated by the variation of the aggregate form is overlarge, misleading effect on the design of the mixing ratio in the engineering is easily generated, and the like exist.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method and a system for preparing standard artificial aggregate by using an additive technology.
In order to achieve the purpose, the invention provides the following scheme:
a method of preparing standard artificial aggregate using additive technology, comprising:
obtaining evaluation indexes of the natural aggregate; the evaluation index includes: a particle size index, a particle type index, and an angularity index;
determining the three-dimensional form of the natural aggregate according to the evaluation index;
based on the three-dimensional shape of the natural aggregate, acquiring a distribution rule of shape parameters of the natural aggregate by adopting a statistical method; the morphological parameters of the natural aggregate comprise: flatness and ellipticity;
determining standard morphological parameters of the aggregate based on the distribution rule;
based on the standard morphological parameters of the aggregate, obtaining a standard model through reverse search positioning;
and 3D printing is carried out on the natural aggregate based on the standard model to prepare the standard aggregate.
Preferably, the acquiring, based on the three-dimensional shape of the natural aggregate, the distribution rule of the shape parameters of the natural aggregate by using a statistical method specifically includes:
collecting three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate by adopting a three-dimensional scanning technology;
determining the flatness and the ellipticity of the natural aggregate according to the three-dimensional point cloud information, and drawing a probability distribution map based on the flatness and the ellipticity.
Preferably, the determining of the standard morphological parameters of the aggregate based on the distribution rule specifically includes:
acquiring probability distribution data of flatness and probability distribution data of ellipticity in the probability distribution map;
performing Gaussian distribution fitting on the probability distribution data of the flattening rate and the probability distribution data of the ellipticity to obtain standard morphological parameters of the aggregate; the standard morphological parameters of the aggregate include: a mathematical expectation of the applanation rate and a mathematical expectation of the ellipticity.
Preferably, the preparing of the standard aggregate by performing 3D printing on the natural aggregate based on the standard model specifically includes:
determining a minimum particle size according to the standard model;
determining a scaling factor based on the minimum particle size;
based on the scaling coefficient, the grain size of the standard model is scaled down or enlarged to obtain three-dimensional models in different grain size ranges;
acquiring a printing condition; the printing conditions include: the hardness, compressive strength and Poisson's ratio parameters of the natural aggregate, the printing precision requirement and the mechanical property requirement of the asphalt pavement horizon applied by the standard aggregate;
selecting a 3D printing process and raw materials according to the printing conditions;
and preparing a standard aggregate according to the selected 3D printing process and the raw materials based on the three-dimensional model.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a method for preparing standard artificial aggregate by using an additive technology, which comprises the steps of determining the three-dimensional form of natural aggregate according to the obtained evaluation index, obtaining the distribution rule of the form parameters of the natural aggregate by adopting a statistical method based on the three-dimensional form of the natural aggregate, determining the standard form parameters of the aggregate based on the distribution rule, obtaining a standard model by reverse search and positioning based on the standard form parameters of the aggregate, and finally carrying out 3D printing on the natural aggregate based on the standard model to obtain the standard aggregate, so that the problems that the discreteness of the test result of a mixture generated by the form variation of the aggregate is overlarge, the misleading effect on the mix proportion design in engineering is easily generated and the like are solved, and the direction is provided for guiding the improvement of an aggregate processing technology.
Corresponding to the method for preparing the standard artificial aggregate by applying the additive technology, the invention also correspondingly provides the following real-time system:
a system for preparing standard man-made aggregate using additive technology, comprising:
the evaluation index acquisition module is used for acquiring evaluation indexes of the natural aggregates; the evaluation index includes: a particle size index, a particle type index, and an angularity index;
the three-dimensional shape determining module is used for determining the three-dimensional shape of the natural aggregate according to the evaluation index;
the distribution rule acquisition module is used for acquiring the distribution rule of the morphological parameters of the natural aggregates by adopting a statistical method based on the three-dimensional morphology of the natural aggregates; the morphological parameters of the natural aggregate comprise: flatness and ellipticity;
the morphological parameter determination module is used for determining standard morphological parameters of the aggregate based on the distribution rule;
the standard model determining module is used for obtaining a standard model through reverse search positioning based on the standard morphological parameters of the aggregate;
and the standard aggregate preparation module is used for carrying out 3D printing on the natural aggregate based on the standard model to prepare a standard aggregate.
Preferably, the distribution rule obtaining module specifically includes:
the three-dimensional point cloud information acquisition unit is used for acquiring the three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate by adopting a three-dimensional scanning technology;
and the probability distribution map drawing unit is used for determining the flatness and the ellipsoid of the natural aggregate according to the three-dimensional point cloud information and drawing a probability distribution map based on the flatness and the ellipsoid.
Preferably, the morphological parameter determination module specifically includes:
a probability distribution data acquisition unit for acquiring probability distribution data of flatness and probability distribution data of ellipticity in the probability distribution map;
the morphological parameter determination unit is used for carrying out Gaussian distribution fitting on the probability distribution data of the flattening rate and the probability distribution data of the ellipticity to obtain standard morphological parameters of the aggregate; the standard morphological parameters of the aggregate include: a mathematical expectation of the flattening and a mathematical expectation of the ellipticity.
Preferably, the standard aggregate preparation module specifically comprises:
a minimum particle size determination unit for determining a minimum particle size according to the standard model;
a scaling factor determining unit for determining a scaling factor based on the minimum particle size;
the three-dimensional model determining unit is used for scaling down or amplifying the grain size of the standard model according to the scaling coefficient to obtain three-dimensional models in different grain size ranges;
a print condition acquisition unit configured to acquire a print condition; the printing conditions include: the hardness, compressive strength and Poisson's ratio parameters of the natural aggregate, the printing precision requirement and the mechanical property requirement of the asphalt pavement horizon applied by the standard aggregate;
a selection unit for selecting a 3D printing process and raw materials according to the printing conditions;
and the standard aggregate preparation unit is used for preparing standard aggregates according to the selected 3D printing process and the raw materials based on the three-dimensional model.
The technical effect achieved by the system for preparing the standard artificial aggregate by using the additive technology is the same as that achieved by the method for preparing the standard artificial aggregate by using the additive technology, so that the detailed description is omitted.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a method of preparing standard artificial aggregate using additive technology provided by the present invention;
FIG. 2 is a three-dimensional reconstruction diagram of a stone crushing model provided by an embodiment of the invention;
FIG. 3 is an aggregate morphology analysis plot provided by an embodiment of the present invention; wherein (a) in fig. 3 is an aggregate flatness ratio analysis chart; fig. 3 (b) is an aggregate three-dimensional angularity analysis chart;
FIG. 4 is a schematic diagram of a 3D printed standard aggregate provided by an embodiment of the invention;
fig. 5 is a schematic structural diagram of a system for preparing standard artificial aggregate by using an additive technology according to 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.
The invention aims to provide a method and a system for preparing standard artificial aggregate by using an additive technology, which aim to solve the problems of overlarge discreteness of a mixture test result caused by aggregate morphological variation, easiness in misleading the mix proportion design in engineering and the like, and further provide a direction for guiding the improvement of an aggregate processing technology.
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, the present invention is described in detail with reference to the accompanying drawings and the detailed description thereof.
As shown in fig. 1, the method for preparing standard artificial aggregate by using additive technology provided by the invention is characterized by comprising the following steps:
step 100: and obtaining the evaluation index of the natural aggregate. The evaluation indexes include: a particle size index, a particle type index, and an angularity index.
Step 101: and determining the three-dimensional shape of the natural aggregate according to the evaluation index.
Step 102: based on the three-dimensional shape of the natural aggregate, a statistical method is adopted to obtain the distribution rule of the shape parameters of the natural aggregate. The morphological parameters of the natural aggregate include: flattening and ellipticity.
Step 103: and determining standard morphological parameters of the aggregate based on the distribution rule.
Step 104: and obtaining a standard model through reverse search positioning based on the standard morphological parameters of the aggregate.
Step 105: and 3D printing is carried out on the natural aggregate based on a standard model to prepare the standard aggregate.
The preparation of the standard artificial aggregate is based on the premise that natural macadam is evaluated first, and the characteristic value of the standard aggregate is determined according to the morphological characteristic parameters of the aggregate.
In the asphalt mixture, the surface texture of the aggregate has very obvious influence on the performance of the asphalt mixture, generally has obvious surface and edge angles, has small size difference in all directions, is similar to a cube, has obvious slightly convex rough surface aggregate, can be mutually embedded, extruded and locked after rolling and has a large internal friction angle. Under the same conditions, the asphalt mixture composed of the aggregate has higher shear strength and better high-temperature stability than the smooth-surface particles.
Therefore, when evaluating the three-dimensional morphology of the aggregate in step 101, it is necessary to evaluate the aggregate using the following three indexes, respectively, based on the morphological characteristics of the three layers of the aggregate:
(1) The particle size index is as follows: the length, width and height of the aggregate. The particle size index is mainly used for evaluating the size of the aggregate, and is subsequently used for grading the constructed aggregate, such as division and scaling according to the specification sizes of 2.36-4.75mm, 4.75-9.5 mm, 9.5-13.2 mm, 13.2-16 mm, 16-19 mm, 19-26.5 mm and the like. Wherein the content of the first and second substances,
wherein, L is the particle size index, a, b and c are the length, width and height of the external rectangle of the aggregate, and a is more than or equal to b and more than or equal to c.
(2) The particle type index is as follows: the method is mainly used for evaluating the squareness degree of the aggregate. The flatness index of the aggregate is used for evaluation, and the mathematical expression is as follows:
wherein D represents the flattening rate (slender ratio) of the crushed stone, a 'is the longest axial length of the crushed stone, c' is the shortest axial length of the crushed stone, and the value range of D is 0-1. According to the provisions of the test protocol (JTGE 42-2005), when D is less than 0.333, it is considered to be a needle-like particle and evaluated as failing.
(3) The edge angle index: the method is used for evaluating the richness degree of edges and corners of aggregate, and the mathematical expression is as follows:
in the formula, E is a three-dimensional edge angle index, and can also be represented by an ellipsoid index. V 1 Is the three-dimensional volume of the aggregate in mm 3 。V 2 Is an aggregate externally connected with a minimum ellipsoid volume with the unit of mm 3 . The larger the E value is, the higher the contact ratio of the aggregate and the minimum external ellipsoid is, the more rounded the aggregate is, and the poorer the angularity is.
Further, the specific implementation steps of the step 102 are:
according to the three evaluation indexes determined in the foregoing, the three-dimensional form of one natural aggregate can be uniquely evaluated, and therefore, three-dimensional scanning technology (industrial CT scanning or three-dimensional digital optical scanner) is employed to acquire three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate. Specifically, three-dimensional point cloud information of aggregate samples processed in a stone yard is collected by adopting a three-dimensional scanning technology.
And determining the flatness and the ellipticity of the natural aggregate according to the three-dimensional point cloud information, and drawing a probability distribution map based on the flatness and the ellipticity. Specifically, according to the finished aggregate specification classification of the stone yard, the number of samples with the specification of 4.75-9.5 mm (or other specifications such as 2.36-4.75mm, 9.5-13.2 mm, 13.2-16 mm, 16-19 mm, 19-26.5 mm and the like) is selected to be not less than 100, and meanwhile, the representativeness of sampling is ensured in a random sampling mode (respectively taking the materials from the top to the bottom of a stock pile). And respectively calculating the flatness and the ellipticity indexes of the sample, and drawing probability distribution maps of different index intervals (interval intervals of 0.1).
Based on the implementation process of step 102, the implementation process of step 103 includes:
and acquiring probability distribution data of the flattening rate and probability distribution data of the ellipsoid in the probability distribution map.
And performing Gaussian distribution fitting on the probability distribution data of the flatness and the probability distribution data of the ellipsoid to obtain standard morphological parameters of the aggregate. Standard morphological parameters of aggregates include: a mathematical expectation of the flattening and a mathematical expectation of the ellipticity.
Specifically, the processed aggregate has a certain random distribution characteristic, and Gaussian distribution fitting is performed on selected sample flatness rate and ellipsoid index probability distribution data based on a statistical analysis method. The gaussian distribution function is expressed as follows:
where μ is a location parameter and σ is a scale parameter.
Firstly, establishing a maximum likelihood function:
solving for a gaussian distribution is actually the process of maximizing the maximum likelihood function. A solving step of solving the function so as to maximize the function:
(1) The likelihood function is logarithmized.
(2) The derivatives are derived for μ and σ to make the derivative 0.
The method comprises the following two steps:
where μ is the mathematical expectation and σ is the standard deviation of the processed aggregate morphology, with larger σ indicating greater variability in aggregate morphology.
At the moment, a corresponding aggregate scanning model can be obtained through reverse search positioning according to the determined mathematical expected values of the flattening rate and the ellipticity. The mathematical expected values of the flattening and the ellipticity are corresponding standard model form parameters. The aggregate scan model is the standard model in step 104.
Based on the process, the determined standard model is subjected to 3D printing preparation to obtain the standard aggregate with uniform shape. Therefore, the step 105 is implemented as follows:
the minimum particle size was determined according to a standard model. Specifically, the minimum particle size, i.e., the minor axis c "and minor axis b 'of the box which is the smallest circumscribed dimension, is measured according to a standard model determined, and the mesh size through which the b'. Multidot.c" rectangle formed is the minimum particle size of the aggregate. The particle size range of the coarse aggregate can be divided into 4.75-9.5 mm, 9.5-13.2 mm, 13.2-16 mm, 16-19 mm and 19-26.5 mm.
The scaling factor is determined based on the minimum particle size. Specifically, the scaling coefficient of aggregate models in other particle size ranges is determined by taking the minimum particle size of the standard model as a reference, and the mathematical expression is as follows:
k＝d i /d 0
wherein d is 0 Is the reference particle size of the standard model, according to the previous step, d 0 D is the median value of the particle size range of the minimum particle size of the collected standard model, if the minimum particle size of the standard aggregate is in the range of 4.75-9.5 mm 0 ＝(4.75+9.5)/2＝7.125mm。d i If 9.5-13.2 mm standard aggregate is required to be prepared for the median particle size of the target aggregate, the corresponding d i ＝(9.5+13.2)/2＝11.35mm。
And based on the scaling coefficient, the particle size of the standard model is scaled down or enlarged to obtain the three-dimensional model in different particle size ranges. Specifically, the aggregate three-dimensional models with different sizes are determined according to the scanned standard model and the scaling factors of aggregates with other specifications to be printed, and the corresponding proportion is reduced or enlarged.
The print condition is acquired. The printing conditions include: the hardness, compressive strength and Poisson's ratio parameters of the natural aggregate, the printing precision requirement and the mechanical property requirement of the asphalt pavement horizon applied by the standard aggregate.
And selecting a 3D printing process and raw materials according to the printing conditions.
And preparing the standard aggregate according to the selected 3D printing process and raw materials based on the three-dimensional model. Specifically, the acquired point cloud data of the standard model is converted into an STL file and imported into the 3D printing device. After a layer thickness parameter of the printing equipment is selected in a software system of the 3D printing equipment and raw materials required by printing are selected, a supporting parameter is set and the printing work of aggregate is started.
And after the standard aggregate is printed, taking out the printed aggregate solid model, and performing post-treatment such as model maintenance, surface cleaning, polishing and the like.
The following is a detailed description of the principle and process of the present invention for preparing standard artificial aggregate by additive technology. In practice, the following embodiments are included, but not limited thereto.
Step one, aggregate sampling of stone processing field
Aiming at aggregate processing in a stone processing field along a certain high-speed project, aggregate finished products of 4.75-9.5 mm under three processing technologies are respectively collected, and the number of samples is not less than 50. The three processes are as follows: pure impact crushing, namely jaw crushing, cone crushing and impact crushing. And a second process: pure shaping processing, namely jaw crushing, conical crushing and shaping machine. And a third process: 50 percent of impact crushing and 50 percent of shaping process, namely half-and-half mixing of two processed aggregates.
Step two, aggregate three-dimensional scanning
An AutoScanDS-EX three-dimensional scanner is adopted to scan the aggregate sample, and the method mainly comprises the following steps:
A. aggregate pretreatment: the natural macadam is simply pretreated to remove impurities such as dust on the surface of the macadam. The pretreated gravels are partially reflective, and partially quartz stone and other components are black and too dark, so that the two conditions are not favorable for completing three-dimensional scanning. The experiment solves the problem of light reflection by coating a thin layer of zirconia powder with the particle size of 50nm on the surface of the crushed stone. For the sites on the macadam where black and powder are too thin and difficult to scan, a contrast agent is coated on the sites to enhance the scanning effect, so that the dark or reflective parts of the macadam are weakened, and the scanning condition is achieved.
B. Image splicing: and fixing the crushed stone on a scanning table, and scanning the crushed stone by using a three-dimensional scanner to obtain appearance form data of the crushed stone. During scanning, the environment (such as a scanning table) where the gravel is located is inevitably scanned, and the obtained data has a large number of noise points and noisy points and needs data processing to delete the noisy points. And after the noise data is deleted, image splicing is carried out. Because the contact point between the crushed stone and the scanning table cannot be scanned, the upper half part of the crushed stone is scanned firstly in the experiment, then the crushed stone is overturned, and the lower half part of the crushed stone is scanned, so that the experiment needs to adopt a splicing scanning mode, and data are merged after splicing to form a complete three-dimensional image. Because of the existence of noise points in the scanning process, after the image is finished, the computer can automatically perform basic operation according to the surrounding characteristic points, and fill up the vacancy to form a relatively perfect gravel shape.
C. Image restoration and three-dimensional reconstruction: the data obtained by scanning is mainly point cloud data, the point cloud data is changed into model data when a triangular patch is automatically generated, and the point cloud scanning does not only obtain one layer but also has a multilayer overlapping form, so that the point cloud scanning has a certain overlap ratio, and Max software is adopted for repairing the point cloud scanning. After completing hole filling and repairing, the model is basically completed, as shown in fig. 2. And finally converting into STL format or other graphic format.
Thirdly, aggregate form evaluation and standard parameter determination
Randomly selecting about 100 aggregates under each process, respectively counting the sphericity index and the ellipsoidal degree index of the coarse aggregates under the three processing processes, and drawing a probability distribution density chart by taking a sphericity test result interval and an ellipsoidal degree test result interval as abscissa and taking the aggregate proportion of different test result intervals as ordinate, wherein the probability distribution density chart is shown in figure 3. It can be obviously seen that the sphericity and the ellipsoid values of the coarse aggregate under different processing technologies have obvious peak values and show peak state distribution. But the aggregate test results under different processes have different peak states and show off-peak states. The test results were fitted with a gaussian distribution and the statistical results are shown in table 1.
TABLE 1 statistical table of aggregate form indexes
The experimental analysis can obtain:
(1) The flatness and the three-dimensional corner angle of the aggregate form processed in the stone field meet the Gaussian distribution, and the correlation coefficient of fitting can reach more than 0.8.
(2) The standard shape of the aggregate produced by different processes is different, the standard aggregate flatness value of the first process is 0.734, and the three-dimensional angularity value is 0.731. The standard aggregate flatness value of process two is 0.826 and the three-dimensional angularity value is 0.721. The standard aggregate flatness value for process three was 0.785 and the three dimensional angularity value was 0.777.
(3) The aggregate particle type produced by the second process is closer to a cube, and the framework stability of the asphalt mixture is enhanced. The aggregate produced by the first process has richer edges and corners, and is beneficial to enhancing the internal friction of the aggregate of the asphalt mixture.
Step four, preparation of standard aggregate
Scaling in different proportions is carried out by taking the specification size of the selected natural macadam with the diameter of 4.75-9.5 mm as a reference and the median value of the target specification size as a molecule, and the scaling coefficients are summarized in a table 2.
TABLE 2 scaling factor table for different size aggregates
| Serial number | Specification/ | Scaling factor | |
| 1 | 19～26.5 | 3.193 | |
| 2 | 16～19 | 2.456 | |
| 3 | 13.2～16 | 2.049 | |
| 4 | 9.5～13.2 | 1.593 | |
| 5 | 4.75～9.5 | 1 | |
| 6 | 2.36～4.75 | 0.499 |
The photosensitive resin macadam model is molded by using iSLA500 equipment of a photocuring molding SLA technology, the printing layer thickness parameter is set to be 0.1mm, the light spot precision is 0.1-0.5 mm, and the printed macadam model presents a white appearance, which is shown in figure 4. The printing process may be set up as a slab of 36 rubble. According to the requirement of the test, the corresponding amount of standard aggregate can be produced and prepared.
Step five, comparison of mixture standard test
According to the mix proportion of asphalt mixture and cement concrete determined by technical Specification for road asphalt pavement construction (JTGF 40-2004) and detailed Specification for road cement concrete pavement construction (JTGTF 30-2014), tests such as corresponding Marshall stability, splitting strength and rutting of the asphalt mixture are carried out by molding a concrete sample by using standard aggregates according to the operations of test procedures for road engineering asphalt and asphalt mixture (JTGE 20-2011) and test procedures for road engineering cement and cement concrete (JTGE 30-2005). And tests such as compressive strength, elastic modulus and the like of the cement concrete test piece. In engineering projects, on one hand, the influence of the form difference of the standard aggregate on the mechanical property of the mixture test piece under different stone yards and different processing technologies can be compared. On the other hand, the method can be used for carrying out comparison tests among different laboratories, eliminating variation of aggregate, verifying the influence of factors such as instruments, equipment, personnel operation, test environment and the like among different laboratories on test results, and evaluating the quality and reliability of engineering detection data and the operation and management level of the laboratories.
In addition, the invention also provides a system for preparing the standard artificial aggregate by using the additive technology, which corresponds to the method for preparing the standard artificial aggregate by using the additive technology. As shown in fig. 5, the system includes: the system comprises an evaluation index acquisition module 1, a three-dimensional form determination module 2, a distribution rule acquisition module 3, a form parameter determination module 4, a standard model determination module 5 and a standard aggregate preparation module 6.
The evaluation index acquisition module 1 is used for acquiring evaluation indexes of the natural aggregates. The evaluation indexes include: a particle size index, a particle type index, and an angularity index.
The three-dimensional shape determining module 2 is used for determining the three-dimensional shape of the natural aggregate according to the evaluation index.
The distribution rule obtaining module 3 is used for obtaining the distribution rule of the morphological parameters of the natural aggregates by adopting a statistical method based on the three-dimensional morphology of the natural aggregates. The morphological parameters of the natural aggregate include: applanation ratio and ellipticity.
The morphological parameter determination module 4 is used for determining standard morphological parameters of the aggregate based on the distribution rule.
And the standard model determining module 5 is used for obtaining a standard model through reverse search positioning based on the standard morphological parameters of the aggregate.
And the standard aggregate preparation module 6 is used for performing 3D printing on the natural aggregate based on a standard model to prepare a standard aggregate.
Further, the distribution rule obtaining module 3 specifically includes: the device comprises a three-dimensional point cloud information acquisition unit and a probability distribution map drawing unit.
The three-dimensional point cloud information acquisition unit is used for acquiring the three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate by adopting a three-dimensional scanning technology.
And the probability distribution map drawing unit is used for determining the flatness and the ellipticity of the natural aggregate according to the three-dimensional point cloud information and drawing the probability distribution map based on the flatness and the ellipticity.
Further, the morphological parameter determination module 4 specifically includes: a probability distribution data acquisition unit and a morphological parameter determination unit.
The probability distribution data acquisition unit is used for acquiring probability distribution data of the flattening rate and probability distribution data of the ellipticity in the probability distribution map.
The morphological parameter determination unit is used for performing Gaussian distribution fitting on the probability distribution data of the flatness ratio and the probability distribution data of the ellipticity degree to obtain standard morphological parameters of the aggregate. Standard morphological parameters of aggregates include: a mathematical expectation of the applanation rate and a mathematical expectation of the ellipticity.
Further, the standard aggregate preparation module 6 specifically includes: the device comprises a minimum particle size determining unit, a scaling coefficient determining unit, a three-dimensional model determining unit, a printing condition obtaining unit, a selecting unit and a standard aggregate preparing unit.
Wherein the minimum particle size determination unit is used for determining the minimum particle size according to a standard model.
The scaling factor determining unit is used for determining the scaling factor based on the minimum particle size.
And the three-dimensional model determining unit is used for scaling down or amplifying the grain size of the standard model based on the scaling coefficient to obtain the three-dimensional model in different grain size ranges.
The print condition acquisition unit is used for acquiring print conditions. The printing conditions include: the hardness, compressive strength and Poisson's ratio parameters of the natural aggregate, the printing precision requirement and the mechanical property requirement of the asphalt pavement horizon applied by the standard aggregate.
The selection unit is used for selecting a 3D printing process and raw materials according to printing conditions.
And the standard aggregate preparation unit is used for preparing and obtaining standard aggregates according to the selected 3D printing process and raw materials based on the three-dimensional model.
In summary, based on the above, the present invention has the following advantages over the prior art:
1) The form of the aggregate is evaluated by adopting indexes of three layers of grain size, grain type and edge angle, the three-dimensional characteristics of the aggregate can be comprehensively represented, the indexes have uniqueness, and the problem of insufficient representativeness of the conventional two-dimensional profile index of the aggregate is solved.
2) The aggregate sampling analysis method comprises the steps of sampling and analyzing aggregates of different stone fields and different processing technologies, enabling processing forms of the aggregates to have certain random distribution characteristics, fitting flatness and edge angle index probability distribution of the aggregates by using a Gaussian distribution function, enabling fitting correlation coefficients to reach more than 0.8, and having good fitting goodness, wherein the determined flatness and ellipsoid mean values can be used as standard aggregate grain types and edge angle parameters under the characteristic working condition.
3) According to the standard model determined by sampling, a series of aggregate models with different sizes can be generated by calculating the scaling coefficients under different specification particle sizes, and then an entity is prepared by means of a 3D printing technology, and the defects of a lot of natural aggregates are avoided by the 3D printed standard crushed stones. For example, the printed macadam does not contain micro particles, does not contain microcracks, weak joints, weak structural surfaces and the like generated in macadam processing, has uniform texture density and uniform shape, and is compact and does not absorb water.
4) The 3D aggregate is prepared through the standard model, the same form as the natural aggregate can be kept, and a more uniform construction state can be provided when the structure is designed. In the bridge deck pavement project, the density is low (only 1.0-1.5 g/cm < 3 >), and the density is about half of that of natural aggregate, so that the dead load of the bridge deck can be reduced, and the bridge deck pavement project has more obvious application advantages of special road sections.
5) The standard aggregate with uniform shape is used for manufacturing the mixture test piece, the problem of overlarge variation of test results caused by different shapes of the natural aggregate can be solved, the number of test control groups is effectively reduced by at least more than half, the test energy consumption and the test time are effectively saved, and the labor intensity of test workers is reduced.
6) The laboratory comparison test carried out by the standard aggregate can directly show the overall test capability of the laboratory and the test skills of workers, verify the execution scientificity of the laboratory to test programs, methods and other regulations, and improve the reliability of the laboratory.
The embodiments in the present description 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. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the foregoing, the description is not to be taken in a limiting sense.
Claims (4)
1. A method for preparing standard artificial aggregate by using an additive technology is characterized by comprising the following steps:
obtaining evaluation indexes of the natural aggregate; the evaluation index includes: a particle size index, a particle type index, and an angularity index; the particle size indexes are as follows:
wherein L is a particle size index, a is the length of an external rectangle of the aggregate, b is the width of the external rectangle of the aggregate, c is the height of the external rectangle of the aggregate, and a is more than or equal to b and more than or equal to c;
determining the three-dimensional shape of the natural aggregate according to the evaluation index;
based on the three-dimensional form of the natural aggregate, acquiring a distribution rule of form parameters of the natural aggregate by adopting a statistical method; the morphological parameters of the natural aggregate comprise: flatness and ellipticity;
determining standard morphological parameters of the aggregate based on the distribution rule;
obtaining a standard model through reverse search positioning based on the standard morphological parameters of the aggregate;
3D printing is carried out on the natural aggregate based on the standard model to prepare standard aggregate;
the method for acquiring the distribution rule of the morphological parameters of the natural aggregate by adopting a statistical method based on the three-dimensional morphology of the natural aggregate specifically comprises the following steps:
collecting three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate by adopting a three-dimensional scanning technology;
determining the flatness rate and the ellipticity of the natural aggregate according to the three-dimensional point cloud information, and drawing a probability distribution map based on the flatness rate and the ellipticity;
the method for determining the standard morphological parameters of the aggregate based on the distribution rule specifically comprises the following steps:
acquiring probability distribution data of flatness and probability distribution data of ellipticity in the probability distribution map;
performing Gaussian distribution fitting on the probability distribution data of the flattening rate and the probability distribution data of the ellipticity to obtain standard morphological parameters of the aggregate; the standard morphological parameters of the aggregate include: a mathematical expectation of the flattening and a mathematical expectation of the ellipticity.
2. The method for preparing standard artificial aggregate by using additive technology according to claim 1, wherein the step of preparing the standard aggregate by performing 3D printing on the natural aggregate based on the standard model specifically comprises the following steps:
determining a minimum particle size according to the standard model;
determining a scaling factor based on the minimum particle size;
based on the scaling coefficient, the particle size of the standard model is scaled down or enlarged to obtain three-dimensional models in different particle size ranges;
acquiring a printing condition; the printing conditions include: the hardness, compressive strength and Poisson ratio parameters of the natural aggregate, printing precision requirements and mechanical property requirements of an asphalt pavement layer position applied by the standard aggregate;
selecting a 3D printing process and raw materials according to the printing conditions;
and preparing a standard aggregate according to the selected 3D printing process and the raw materials based on the three-dimensional model.
3. A system for preparing standard artificial aggregate using additive technology, comprising:
the evaluation index acquisition module is used for acquiring evaluation indexes of the natural aggregates; the evaluation index includes: a particle size index, a particle type index, and an angularity index; the particle size indexes are as follows:
wherein L is a particle size index, a is the length of an external rectangle of the aggregate, b is the width of the external rectangle of the aggregate, c is the height of the external rectangle of the aggregate, and a is more than or equal to b and more than or equal to c;
the three-dimensional shape determining module is used for determining the three-dimensional shape of the natural aggregate according to the evaluation index;
the distribution rule acquisition module is used for acquiring the distribution rule of the morphological parameters of the natural aggregates by adopting a statistical method based on the three-dimensional morphology of the natural aggregates; the morphological parameters of the natural aggregate comprise: flatness and ellipticity;
the morphological parameter determination module is used for determining standard morphological parameters of the aggregate based on the distribution rule;
the standard model determining module is used for obtaining a standard model through reverse search positioning based on the standard morphological parameters of the aggregate;
the standard aggregate preparation module is used for performing 3D printing on the natural aggregate based on the standard model to prepare a standard aggregate;
the distribution rule obtaining module specifically includes:
the three-dimensional point cloud information acquisition unit is used for acquiring the three-dimensional point cloud information of the natural aggregate based on the three-dimensional form of the natural aggregate by adopting a three-dimensional scanning technology;
the probability distribution map drawing unit is used for determining the flatness and the ellipticity of the natural aggregate according to the three-dimensional point cloud information and drawing a probability distribution map based on the flatness and the ellipticity;
the morphological parameter determination module specifically comprises:
a probability distribution data acquisition unit for acquiring probability distribution data of flatness and probability distribution data of ellipticity in the probability distribution map;
the morphological parameter determination unit is used for performing Gaussian distribution fitting on the probability distribution data of the flattening rate and the probability distribution data of the ellipticity to obtain standard morphological parameters of the aggregate; the standard morphological parameters of the aggregate include: a mathematical expectation of the flattening and a mathematical expectation of the ellipticity.
4. The system for preparing standard artificial aggregates by using the additive technology according to claim 3, wherein the standard aggregate preparation module specifically comprises:
a minimum particle size determination unit for determining a minimum particle size according to the standard model;
a scaling factor determining unit for determining a scaling factor based on the minimum particle size;
the three-dimensional model determining unit is used for scaling down or amplifying the grain size of the standard model to obtain three-dimensional models in different grain size ranges based on the scaling coefficient;
a print condition acquisition unit configured to acquire a print condition; the printing conditions include: the hardness, compressive strength and Poisson ratio parameters of the natural aggregate, printing precision requirements and mechanical property requirements of an asphalt pavement layer position applied by the standard aggregate;
a selection unit for selecting a 3D printing process and raw materials according to the printing conditions;
and the standard aggregate preparation unit is used for preparing standard aggregates according to the selected 3D printing process and the raw materials based on the three-dimensional model.
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