CN114757072A - Grain humidification uniformity quantitative detection method and system in spray tempering process - Google Patents
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Abstract
The invention provides a method and a system for quantitatively detecting the grain humidification uniformity in a spray tempering process, which are used for quantitatively, accurately and quickly detecting the grain humidification uniformity in the spray tempering process under a complex tank body environment and a humidification condition. The grain humidification uniformity quantitative detection method in the spray tempering process comprises the following steps: step 1, establishing a discrete element numerical model of the grain particles and the mixing machine tank body; step 2, determining material parameters and contact parameters of the grain particles and the mixer tank body as model basic parameters; step 3, obtaining discrete element simulation parameter-grain particle water content combined data according to the model basic parameters, and calibrating a water content equation by adopting the discrete element simulation parameter-grain particle water content combined data; step 4, inputting the combination data of the mixing parameter and the humidification uniformity, and calibrating a humidification uniformity model equation; and 5, inputting the mixing parameter variable under the condition to be measured into the calibrated humidification uniformity model equation, and predicting to obtain grain humidification uniformity data under the condition.
Description
Technical Field
The invention belongs to the technical field of grain processing simulation, and particularly relates to a grain humidification uniformity quantitative detection method and system in a spray tempering process.
Background
In the production and processing processes of grains such as rice, wheat and the like, continuous humidification and tempering operations are required to be carried out on the grains, and the process is also widely applied to the pretreatment process of other grain processing. The humidification tempering process can enable different grain particles to reach the water content meeting the processing requirement, thereby improving the product quality. The uneven moisture content after humidification leads to excessive or insufficient local humidification of the grains: when the local humidification is uneven, the grain surface absorbs more moisture and generates stress cracks due to the increase of the difference of the water inside and outside the grain; the local soaking environment can be formed when the local humidification quantity is too large, so that the quality of the grains is reduced; when the local humidification is insufficient, the grain can not achieve the humidification purpose. Therefore, the humidification uniformity is an important index for testing the performance of the humidification tempering process. In recent years, an increasing number of students have been paying attention to the study of the humidification homogeneity index detection and evaluation method.
At present, the common grain humidifying and tempering processes mainly comprise a counter-current circulating type process and a cross-current circulating type process. In order to detect the humidification uniformity, a sampling method is generally adopted for statistical test, the randomness of the test method is high, the difficulty of obtaining samples is high for factors such as different humidification processes, different grain particle attributes, different mixer structures and parameters, and the like, and the detection result is also inaccurate.
Disclosure of Invention
The invention is carried out to solve the problems, and aims to provide a method and a system for quantitatively detecting the humidification uniformity of grains in a spray tempering process, which can be suitable for quantitatively, accurately and quickly detecting the humidification uniformity of grains in the spray tempering process under a complex tank body environment and humidification conditions.
In order to achieve the purpose, the invention adopts the following scheme:
< method >
The invention provides a grain humidification uniformity quantitative detection method in a spray tempering process, which is characterized by comprising the following steps of:
step 1, establishing a three-dimensional discrete element numerical model of the grain particles and the mixing machine tank body according to structural size data of the grain particles to be detected and the mixing machine tank body;
step 2, determining material parameters of the grains and the mixing machine tank body and contact parameters between the grains and the mixing machine tank body and between the grains and the mixing machine tank body according to physical property data of the grains to be detected and the mixing machine tank body, and taking the material parameters and the contact parameters as model basic parameters; the material parameters include: particle density, particle poisson ratio, particle shear modulus, tank density, tank poisson ratio and tank shear modulus; the contact parameters include: the coefficient of restitution among the particles, the coefficient of static friction among the particles, the coefficient of kinetic friction among the particles, the coefficient of restitution between the particles and the inner wall of the tank body, the coefficient of static friction between the particles and the inner wall of the tank body and the coefficient of kinetic friction between the particles and the inner wall of the tank body;
Step 3, discrete element simulation parameters-grain particle water content combined data under different water contents are obtained according to model basic parameters, a water content equation representing the mapping relation between the grain wet particle water content and the discrete element simulation parameters is established, each undetermined constant in the water content equation is calibrated by adopting the discrete element simulation parameters-grain particle water content combined data, and a calibrated water content equation is obtained; the discrete element simulation parameters comprise surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient;
step 4, discrete element simulation parameters in the moisture content equation calibrated in the step 3 are adopted to represent the moisture content, mixed parameters are input to carry out particle system simulation, the mixed parameters comprise particle moisture content, particle size, working parameters and tank structure parameters, the working parameters comprise at least one of rotating speed, filling rate and mixing time, the tank structure parameters comprise at least one of positive and negative rotation, staggered blades, blade number and blade length, and mixed parameter-humidification uniformity combined data under different mixed parameters are obtained; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the combined data of the mixing parameters and the humidification uniformity, and calibrating each undetermined constant of the humidification uniformity model equation to obtain a calibrated humidification uniformity model equation;
And 5, inputting the mixing parameter variable under the condition to be measured into the calibrated humidification uniformity model equation, and predicting to obtain grain humidification uniformity data under the condition.
Preferably, the grain humidification uniformity quantitative detection method in the spray tempering process provided by the invention can also have the following characteristics: in the step 1, three-dimensional modeling software is used for modeling the grain particles and the mixer tank body model, dividing grids, setting boundary conditions and exporting a model file, and then the model file is imported into discrete element numerical simulation software. The three-dimensional modeling software can be any one of Solidworks and Pro/E, CATIA, and the discrete element numerical simulation software is EDEM.
Preferably, the grain humidification uniformity quantitative detection method in the spray tempering process provided by the invention can also have the following characteristics: in step 2, model basis parameter setting: and setting material parameters of the particles and the mixer tank and contact parameters between the particles and the mixer tank in discrete element simulation software, and taking the JKR model as a particle-to-particle contact model and a particle-to-mixer tank contact model.
Preferably, the grain humidification uniformity quantitative detection method in the spray tempering process provided by the invention can also have the following characteristics: in step 3, the model basic parameters are input into the cohesion model to obtain discrete element simulation parameter-grain particle water content combined data under different water contents.
Preferably, the method for quantitatively detecting the humidification uniformity of the grains in the spray tempering process, provided by the invention, further has the following characteristics that in the step 3, the established moisture content equation is as follows:
y1＝a0+a1x1+a2x2+a3x3+a4x4，
in the formula, y1Is the water content, x, of the wet granules1Is surface energy, x2Coefficient of restitution for collision, x3The coefficient of static friction between particles, x4Is the coefficient of rolling friction between particles, a0～a4Is a undetermined constant.
Preferably, the method for quantitatively detecting the humidification uniformity of the grains in the spray tempering process, provided by the invention, can also have the following characteristics: in step 4, humidifying, tempering and numerical simulation: inputting discrete element simulation parameters of surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient in particle system simulation software, wherein each group of discrete element simulation parameters corresponds to the water content of one grain particle; adding the same number of dry and wet grains with different water contents under the condition of certain mixing parameters to carry out humidification conditioning numerical simulation tests, and respectively marking the same-attribute grain dry and wet grains with equal grain diameters as different colors in an initial state; and (3) quantitatively analyzing the particle distribution data in the simulation software by adopting a separation index method, and quantitatively representing the humidification uniformity of the grains.
Preferably, the grain humidification uniformity quantitative detection method in the spray tempering process provided by the invention can also have the following characteristics: in step 4, the established humidification uniformity model equation is:
z＝b0+b1y1+b2y2y3+b3y4+b4y5+b5y6y7y8+b6y9，
wherein z is humidification uniformity, y1Is the moisture content of the wet granules, y2Is the particle size, y3As filling ratio, y4Is the rotational speed, y5As mixing time, y6The positive and negative rotation is carried out, the positive rotation takes 1, the negative rotation takes-1, y7Whether the blades are staggered or not is 1, and whether the blades are staggered or not is-1, y8Number of blades, y9Is the length of the blade, b0～b6Is a undetermined constant.
< System >
Further, the present invention provides a system for quantitatively detecting grain humidification uniformity in a spray tempering process, which can automatically implement the above < method >, and is characterized by comprising:
the model component part is used for establishing a three-dimensional discrete element numerical model of the grain particles and the mixing machine tank body according to the structural size data of the grain particles to be detected and the mixing machine tank body;
a basic parameter determining part for determining material parameters of the grain particles and the mixing machine tank body and contact parameters between the grain particles and the mixing machine tank body according to the physical property data of the grain particles to be detected and the mixing machine tank body, and taking the material parameters and the contact parameters as model basic parameters; the material parameters include: particle density, particle poisson ratio, particle shear modulus, tank density, tank poisson ratio, and tank shear modulus; the contact parameters include: the coefficient of restitution among the particles, the coefficient of static friction among the particles, the coefficient of kinetic friction among the particles, the coefficient of restitution between the particles and the inner wall of the tank body, the coefficient of static friction between the particles and the inner wall of the tank body, and the coefficient of kinetic friction between the particles and the inner wall of the tank body;
The water content equation building part is used for obtaining discrete element simulation parameter-grain particle water content combined data under different water contents according to the model basic parameters, building a water content equation representing the mapping relation between the water content of the grain wet particles and the discrete element simulation parameters, and calibrating each undetermined constant in the water content equation by adopting the discrete element simulation parameter-grain particle water content combined data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient;
a humidifying uniformity model equation building part, which is used for representing the water content by discrete element simulation parameters in a calibrated water content equation, inputting mixed parameters for simulation of a particle system, wherein the mixed parameters comprise particle water content, particle size, working parameters and tank structure parameters, the working parameters comprise at least one of rotating speed, filling rate and mixing time, and the tank structure parameters comprise at least one of positive and negative rotation, whether blades are staggered, the number of the blades and the length of the blades, so as to obtain the combined data of the mixing parameters and humidifying uniformity under different mixed parameters; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the mixing parameter-humidification uniformity combined data, calibrating each undetermined constant of the humidification uniformity model equation, and obtaining a calibrated humidification uniformity model equation;
The quantitative detection part inputs the mixing parameter variable under the condition to be detected into the calibrated humidification uniformity model equation, and grain humidification uniformity data under the condition are obtained through prediction; and
and the control part is in communication connection with the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part and the quantitative detection part and controls the operation of the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part and the quantitative detection part.
Preferably, the system for quantitatively detecting the grain humidification uniformity in the spray tempering process, provided by the invention, can further comprise: and the input display part is in communication connection with the control part, enables a user to input information for detection and an operation instruction, and performs corresponding display according to the operation instruction.
Preferably, the quantitative detection system for grain humidification uniformity in the spray tempering process provided by the invention can also have the following characteristics: the input display part enables a user to input structural dimension data and physical property data of the grain particles to be detected and the mixing machine tank body, and can be used for operating according to corresponding operation instructions: displaying a three-dimensional discrete element numerical model of the grain particles and the mixer tank body built by the model component part, displaying the material parameters and the contact parameters determined by the basic parameter determination part in a list form or on a three-dimensional discrete element numerical model diagram, displaying discrete element simulation parameters-grain particle water content combined data and a built water content equation obtained by the water content equation building part, displaying the mixed parameter-humidification uniformity combined data and the built humidification uniformity model equation obtained by the humidification uniformity model equation building part, displaying the grain humidification uniformity data predicted by the quantitative detection part, corresponding conditions to be detected and mixed parameter variables in a list form or on a three-dimensional discrete element numerical model diagram in a correlation manner, and displaying different grain particles in a color difference selected by a user according to dry and wet conditions, and the humidity change condition of the grain particles in the spray tempering process can be dynamically displayed.
Action and effects of the invention
The method and the system for quantitatively detecting the grain humidifying uniformity in the spray tempering process can be suitable for quantitatively detecting the grain humidifying uniformity in the spray tempering process under the complex tank body environments of different humidifying processes, different grain particle attributes, different mixer structures and parameters and the like, can sample and detect the humidifying uniformity at any time, and have the advantages of very simple measuring process, visual and accurate measuring result and no damage to samples in the measuring process. Has very important significance and value for regulating and controlling the uniformity of humidification and tempering, improving the quality of grains and optimally designing the mixing parameters of humidification and tempering equipment.
Drawings
FIG. 1 is a flow chart of a grain humidification uniformity quantitative determination method in a spray tempering process according to an embodiment of the invention;
FIG. 2 is a numerical model diagram of brown rice grains according to a first embodiment of the present invention;
FIG. 3 is a diagram of a numerical model of a can body according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a mixing state of particles at the end of simulation according to a first embodiment of the present invention;
FIG. 5 is a graph of the degree of mixing of particles involved in a first embodiment of the present invention;
FIG. 6 is a numerical model diagram of brown rice grains according to a second embodiment of the present invention;
FIG. 7 is a diagram showing a state of mixing of particles at the end of simulation according to the second embodiment of the present invention;
FIG. 8 is a graph showing the degree of mixing of particles according to the second embodiment of the present invention.
Detailed Description
The following describes specific embodiments of the method and system for quantitatively detecting grain humidification uniformity in spray tempering according to the present invention in detail with reference to the accompanying drawings.
< first embodiment >
As shown in fig. 1, the method for quantitatively detecting the humidification uniformity of grains in the spray tempering process provided in the first embodiment specifically comprises the following steps:
modeling the particle and mixer models, dividing grids, setting boundary conditions and exporting model files by utilizing SolidWorks2019 software, and importing the model files into EDEM discrete element simulation software. Taking the brown rice as a particle prototype, as shown in fig. 2, the established particle numerical model is an elliptical model with a major axis of 6mm and a minor axis of 3.125 mm. A numerical model of a mixer tank is shown in figure 3. Simulation parameters such as material properties of the particles and the mixer tank and the collision coefficient between them were then set in the EDEM software, as detailed in table 1 below.
TABLE 1 simulation of desired parameters
The JKR cohesion model was used as a particle-to-particle, particle-to-mixer contact model. The method comprises the steps of calibrating the moisture content of wet brown rice by using a JKR model, firstly carrying out a stacking test on 37 groups of brown rice with the moisture content of 12-30% and the interval of 0.5%, and determining the true stacking angle corresponding to the moisture content of the wet brown rice particles; and (4) obtaining a discrete element simulation parameter combination (surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient) corresponding to the simulation stacking angle and the moisture content of the wet particles by taking the real stacking angle as an evaluation index. Analyzing the test result by using Design-Expert software, and establishing a correlation equation between the moisture content of the brown rice wet particles and the significance discrete element simulation parameters by taking the stacking angle as an intermediate variable as follows:
y1＝19.8+3.62x1-1.75x2+0.56x3+0.25x4，
In the formula, y1Is the water content, x, of the wet granules1Is surface energy, x2Coefficient of restitution for collision, x3The coefficient of static friction between particles, x4The coefficient of rolling friction between particles. Moisture content and dispersion of wet granulesR of meta-simulation parameters2And was 0.81.
And then inputting 2 groups of brown rice particles with different water contents in a discrete element simulation environment (in EDEM simulation software, the calibrated discrete element simulation parameter combination is used as an input parameter to represent the water content of the brown rice particles), wherein the water contents of the 2 groups of particles are respectively 14.5% and 15.5%. A humidification simulation test is carried out according to the method. The properties and the quantity of the brown rice grains in the 2 groups are completely the same. The mixing parameters were set as follows: the particle sizes of the particles are all 3.8 mm; the rotating speed is 20r/min, 30r/min and 40 r/min; the filling rate is 40.2%, 50.5% and 60.8%; mixing time 45S; the blades are staggered in the same rotation mode, the number of the blades is 3, and the length of each blade is 165mm, 175mm and 185 mm. The dry and wet granules with the same particle size and the same property are respectively marked as red and blue layers in an initial state. After the particle layer is stabilized, the stirring blade is rotated at a set angular velocity. At the end of the simulation experiment, the particle data distribution data shown in fig. 4 was derived from the simulation software. According to the particle distribution data derived from the simulation software, the grain humidification uniformity is quantitatively represented by taking the separation index as an index, and the separation index is shown in fig. 5.
Establishing a model equation of mixing parameters and humidification uniformity as follows:
z＝0.39-0.15y1+0.027y2y3+0.0013y4-0.00005y5-0.0073y6y7y8+0.0026y9，
wherein z is humidification uniformity (separation index characterizes humidification uniformity), y1Is the moisture content of the wet granules, y2Is the particle size, y3As filling ratio, y4Is the rotational speed, y5For mixing time, y6For positive and negative rotation, take 1 in positive rotation and take-1, y in negative rotation7Whether the blades are staggered or not is 1, and whether the blades are staggered or not is-1, y8Number of blades, y9Is the blade length.
Predicting according to the humidification uniformity model equation to obtain: the water content of the particles is 0.15, the particle sizes of the particles are all 3.8mm, the rotating speed is 30r/min, the filling rate is 48.6 percent, the mixing time is 48S, the blade length is 180mm, the humidification uniformity is 0.78 under the mixing conditions of inversion, blade staggering and 4 blades. The humidifying uniformity result of the real humidifying and tempering test is 0.81. The relative error is 3.85%, which shows that the humidification uniformity model equation has better accuracy and reliability.
< example two >
As shown in fig. 1, the method for quantitatively detecting the humidification uniformity of grains in the spray tempering process provided in the second embodiment specifically comprises the following steps:
modeling the particle and mixer models, dividing grids, setting boundary conditions and exporting model files by utilizing SolidWorks2019 software, and importing the model files into EDEM discrete element simulation software. The brown rice was used as a prototype of the granule, and the numerical model of the granule was an oval model having a major axis of 7.063mm and a minor axis of 2.750mm (FIG. 6). A numerical model of the mixer tank is shown in figure 3. The material properties of the granules and the mixer tank and the collision coefficient between them were then set in the EDEM software (table 1).
The JKR cohesion model was used as a particle-to-particle, particle-to-mixer contact model. The water content of the wet granules is calibrated by applying a JKR model, firstly, a stacking test is carried out on 37 groups of brown rice with the whole water content of 12-30% and the interval of 0.5%, and a real stacking angle corresponding to the water content of the wet granules of the brown rice is measured; and (4) obtaining a discrete element simulation parameter combination (surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient) corresponding to the simulation stacking angle and the moisture content of the wet particles by taking the real stacking angle as an evaluation index. Establishing a correlation equation between the moisture content of the brown rice wet particles and the significant discrete element simulation parameters by taking the stacking angle as an intermediate variable, wherein the correlation equation comprises the following steps:
y1＝23.5-1.86x1+0.93x2-3.58x3+2.93x4，
in the formula, y1Is the water content, x, of the wet granules1Is surface energy, x2Coefficient of restitution for collision, x3Is the coefficient of static friction, x, between particles4The coefficient of rolling friction between particles. Moisture content of wet particles and R of discrete element simulation parameters2Is 0.93.
And then inputting 2 groups of brown rice particles with different water contents in a discrete element simulation environment (in EDEM simulation software, the calibrated discrete element simulation parameter combination is used as an input parameter to represent the water content of the brown rice particles), wherein the water contents of the 2 groups of particles are respectively 23.5% and 25.5%. A humidification simulation test is carried out according to the method. The properties and the quantity of the brown rice grains in the 2 groups are completely the same. The mixing parameters were set as follows: the particle sizes of the particles are all 4.5 mm; the rotating speed is 20r/min, 30r/min and 40 r/min; the filling rate is 41.1%, 52.9% and 61.8%; mixing time 45S; the blades are reversely rotated and staggered, the number of the blades is 4, and the lengths of the blades are 170mm, 180mm and 190 mm. The dry and wet granules with the same particle size and the same property are respectively marked as red and blue layers in an initial state. After the particle layer is stabilized, the stirring blade is rotated at a set angular velocity. At the end of the simulation experiment, particle data distribution data as shown in fig. 7 was derived from the simulation software. According to the particle distribution data derived from the simulation software, the grain humidification uniformity is quantitatively represented by taking the separation index as an index, and the separation index is shown in fig. 8.
Establishing a model equation of mixing parameters and humidification uniformity as follows:
z＝0.47+0.16y1+0.03y2y3-0.001y4-0.00006y5-0.006y6y7y8+0.0019y9，
wherein z is humidification uniformity (separation index characterizes humidification uniformity), y1Is the moisture content of the wet granules, y2Is the particle size, y3As filling ratio, y4Is the rotational speed, y5As mixing time, y6The positive and negative rotation is carried out, the positive rotation takes 1, the negative rotation takes-1, y7If the leaves are staggered, 1 is taken, and-1, y is not taken8Number of blades, y9Is the blade length.
Predicting according to the humidification uniformity model equation to obtain: the water content of the particles is 0.245, the particle sizes of the particles are all 4.5mm, the rotating speed is 40r/min, the filling rate is 62.6 percent, the mixing time is 45S, the blade length is 175mm, the blades rotate forwards and are staggered, and the humidification uniformity is 0.86 under the mixing condition that the number of the blades is 3. The humidifying uniformity result of the real humidifying and tempering test is 0.82. The relative error is 4.65%, which shows that the humidification uniformity model equation has better accuracy and reliability.
The above examples all prove that the method can be used for quantitative analysis of grain humidification uniformity in spray tempering processes in complex tank environments of different humidification processes, different grain particle attributes, different mixer structures and parameters and the like. The measurement data and the measurement result show that the grain humidifying uniformity can be rapidly, simply and accurately detected by utilizing the correlation between the mixing parameters and the humidifying uniformity in the discrete element simulation environment, and a rapid and accurate detection method is provided for detecting the grain humidifying uniformity in the spray conditioning process.
Further, the embodiment also provides a grain humidification uniformity quantitative detection system capable of automatically realizing the method in the spray tempering process, and the system comprises a model component part, a basic parameter determining part, a water content equation constructing part, a humidification uniformity model equation constructing part, a quantitative detection part, an input display part and a control part.
The model component part establishes a three-dimensional discrete element numerical model of the grain particles and the mixing machine tank body according to the structural size data of the grain particles to be measured and the mixing machine tank body.
A basic parameter determining part determines material parameters of the grain particles and the mixing machine tank body and contact parameters between the grain particles and the mixing machine tank body and between the grain particles and the mixing machine tank body according to physical property data of the grain particles to be detected and the mixing machine tank body, and takes the material parameters and the contact parameters as model basic parameters; the material parameters include: particle density, particle poisson ratio, particle shear modulus, tank density, tank poisson ratio, and tank shear modulus; the contact parameters include: the coefficient of restitution among the particles, the coefficient of static friction among the particles, the coefficient of kinetic friction among the particles, the coefficient of restitution between the particles and the inner wall of the tank body, the coefficient of static friction between the particles and the inner wall of the tank body, and the coefficient of kinetic friction between the particles and the inner wall of the tank body.
The water content equation building part obtains discrete element simulation parameters-grain particle water content combined data under different water contents according to the model basic parameters, establishes a water content equation representing the mapping relation between the water content of the grain wet particles and the discrete element simulation parameters, and calibrates each undetermined constant in the water content equation by adopting the discrete element simulation parameters-grain particle water content combined data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient.
The humidification uniformity model equation building part adopts discrete element simulation parameters in a calibrated water content equation to express the water content, inputs mixing parameters to carry out particle system simulation, the mixing parameters comprise particle water content, particle size, working parameters and tank structure parameters, the working parameters comprise at least one of rotating speed, filling rate and mixing time, the tank structure parameters comprise at least one of positive and negative rotation, whether the blades are staggered, the number of the blades and the length of the blades, and combined data of the mixing parameters and humidification uniformity under different mixing parameters are obtained; establishing a humidification uniformity model equation representing the mapping relation between the mixing parameters and the humidification uniformity, inputting the mixing parameter-humidification uniformity combined data, calibrating each undetermined constant of the humidification uniformity model equation, and obtaining the calibrated humidification uniformity model equation.
And the quantitative detection part inputs the mixing parameter variable under the condition to be detected into the calibrated humidification uniformity model equation, and grain humidification uniformity data under the condition is obtained through prediction.
The input display part is used for allowing a user to input information for detection and an operation instruction and performing corresponding display according to the operation instruction. For example, the input display unit enables the user to input the structural size data and physical property data of the cereal grains to be measured and the mixer tank, and enables the user to perform the following operations according to the corresponding operation instructions: displaying a three-dimensional discrete element numerical model of the grain particles and the mixer tank body established by the model component part, displaying material parameters and contact parameters determined by the basic parameter determining part in a list form or on a three-dimensional discrete element numerical model diagram, displaying discrete element simulation parameter-grain particle water content combined data and a constructed water content equation obtained by the water content equation constructing part, displaying mixed parameter-humidification uniformity combined data and a constructed humidification uniformity model equation obtained by the humidification uniformity model equation constructing part, displaying grain humidification uniformity data and corresponding to-be-measured conditions and mixed parameter variables predicted by the quantitative detection part in a list form or on a three-dimensional discrete element numerical model diagram in a correlation manner, and displaying different grain particles in a color selected by a user according to dry and wet conditions in a distinguishing manner, and the change condition of the grain humidity in the spray tempering process can be dynamically displayed.
The control part is in communication connection with the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part, the quantitative detection part and the input display part to control the operation of the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part, the quantitative detection part and the input display part.
The above embodiments are merely illustrative of the technical solutions of the present invention. The method and system for quantitatively detecting the humidification uniformity of grains in the spray tempering process are not limited to the contents described in the above embodiments, but are subject to the scope defined by the claims. Any modification or supplement or equivalent replacement made by a person skilled in the art on the basis of this embodiment is within the scope of the invention as claimed in the claims.
Claims (10)
1. The method for quantitatively detecting the humidifying uniformity of the grains in the spray tempering process is characterized by comprising the following steps of:
step 1, establishing a three-dimensional discrete element numerical model of the grain particles and the mixing machine tank body according to structural size data of the grain particles to be detected and the mixing machine tank body;
step 2, determining material parameters of the grain particles and the mixing machine tank body and contact parameters between the grain particles and the mixing machine tank body and between the grain particles and the mixing machine tank body according to physical property data of the grain particles to be detected and the mixing machine tank body, and taking the material parameters and the contact parameters as model basic parameters; the material parameters include: particle density, particle poisson ratio, particle shear modulus, tank density, tank poisson ratio, and tank shear modulus; the contact parameters include: the coefficient of restitution among the particles, the coefficient of static friction among the particles, the coefficient of kinetic friction among the particles, the coefficient of restitution between the particles and the inner wall of the tank body, the coefficient of static friction between the particles and the inner wall of the tank body, and the coefficient of kinetic friction between the particles and the inner wall of the tank body;
Step 3, discrete element simulation parameters-grain particle water content combined data under different water contents are obtained according to the model basic parameters, a water content equation representing the mapping relation between the grain wet particle water content and the discrete element simulation parameters is established, discrete element simulation parameters-grain particle water content combined data are adopted to calibrate each undetermined constant in the water content equation, and a calibrated water content equation is obtained; the discrete element simulation parameters comprise surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient;
step 4, discrete element simulation parameters in the calibrated moisture content equation are adopted to represent the moisture content, mixing parameters are input to carry out particle system simulation, the mixing parameters comprise particle moisture content, particle size, working parameters and tank structure parameters, the working parameters comprise at least one of rotating speed, filling rate and mixing time, the tank structure parameters comprise at least one of positive and negative rotation, staggered blades, blade number and blade length, and mixing parameter-humidification uniformity combined data under different mixing parameters are obtained; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the combined data of the mixing parameters and the humidification uniformity, and calibrating each undetermined constant of the humidification uniformity model equation to obtain a calibrated humidification uniformity model equation;
And 5, inputting the mixing parameter variable under the condition to be measured into the calibrated humidification uniformity model equation, and predicting to obtain grain humidification uniformity data under the condition.
2. The grain humidification uniformity quantitative determination method in the spray tempering process according to claim 1, characterized in that:
in the step 1, three-dimensional modeling software is used for modeling the grain particles and the mixer tank model, dividing grids, setting boundary conditions and exporting a model file, and then the model file is imported into discrete element numerical simulation software.
3. The grain humidification uniformity quantitative determination method in the spray tempering process according to claim 1, characterized in that:
in step 2, setting model basic parameters: and setting material parameters of the particles and the mixer tank and contact parameters between the particles and the mixer tank in discrete element simulation software, and taking the JKR model as a particle-to-particle contact model and a particle-to-mixer tank contact model.
4. The grain humidification uniformity quantitative determination method in the spray tempering process according to claim 1, characterized in that:
in step 3, inputting the model basic parameters into the cohesion model to obtain discrete element simulation parameter-grain particle water content combined data under different water contents.
5. The grain humidification uniformity quantitative determination method in the spray tempering process according to claim 1, characterized in that:
in step 3, the water content equation is established as follows:
y1＝a0+a1x1+a2x2+a3x3+a4x4，
in the formula, y1Is the water content, x, of the wet granules1Is surface energy, x2Coefficient of restitution for collision, x3Is the coefficient of static friction, x, between particles4Is the coefficient of rolling friction between particles, a0～a4Is a undetermined constant.
6. The method for quantitatively detecting the humidifying uniformity of the grains in the spray tempering process according to claim 1, which is characterized in that:
in step 4, humidifying, tempering and numerical simulation: inputting discrete element simulation parameters of surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient in particle system simulation software, wherein each group of discrete element simulation parameters corresponds to the water content of one grain particle; adding the same number of dry and wet grains with different water contents under the condition of certain mixing parameters to carry out humidification conditioning numerical simulation tests, and respectively marking the same-attribute dry and wet grains with equal grain diameters into different colors; and (3) quantitatively analyzing the particle distribution data in the simulation software by adopting a separation index method, and quantitatively representing the humidification uniformity of the grains.
7. The method for quantitatively detecting the humidifying uniformity of the grains in the spray tempering process according to claim 1, which is characterized in that:
In step 4, the established humidification uniformity model equation is as follows:
z＝b0+b1y1+b2y2y3+b3y4+b4y5+b5y6y7y8+b6y9，
wherein z is humidification uniformity, y1Is the moisture content of the wet granules, y2Is the particle size, y3As filling ratio, y4Is the rotational speed, y5For mixing time, y6For positive and negative rotation, take 1 in positive rotation and take-1, y in negative rotation7Whether the blades are staggered or not is 1, and whether the blades are staggered or not is-1, y8Number of blades, y9Is the length of the blade, b0～b6Is a undetermined constant.
8. The quantitative detection system for the grain humidification uniformity in the spray tempering process automatically detects according to the quantitative detection method for the grain humidification uniformity in the spray tempering process in any one of claims 1 to 7, and is characterized by comprising the following steps of:
the model component part is used for establishing a three-dimensional discrete element numerical model of the grain particles and the mixing machine tank body according to the structural size data of the grain particles to be detected and the mixing machine tank body;
a basic parameter determining part for determining material parameters of the grain particles and the mixing machine tank body and contact parameters between the grain particles and the mixing machine tank body according to the physical property data of the grain particles to be detected and the mixing machine tank body, and taking the material parameters and the contact parameters as model basic parameters; the material parameters include: particle density, particle poisson ratio, particle shear modulus, tank density, tank poisson ratio, and tank shear modulus; the contact parameters include: the coefficient of restitution among the particles, the coefficient of static friction among the particles, the coefficient of kinetic friction among the particles, the coefficient of restitution between the particles and the inner wall of the tank body, the coefficient of static friction between the particles and the inner wall of the tank body, and the coefficient of kinetic friction between the particles and the inner wall of the tank body;
The water content equation building part is used for obtaining discrete element simulation parameter-grain particle water content combined data under different water contents according to the model basic parameters, building a water content equation representing the mapping relation between the water content of the grain wet particles and the discrete element simulation parameters, and calibrating each undetermined constant in the water content equation by adopting the discrete element simulation parameter-grain particle water content combined data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient;
a humidifying uniformity model equation building part, which is used for representing the water content by discrete element simulation parameters in a calibrated water content equation, inputting mixed parameters for simulation of a particle system, wherein the mixed parameters comprise particle water content, particle size, working parameters and tank structure parameters, the working parameters comprise at least one of rotating speed, filling rate and mixing time, and the tank structure parameters comprise at least one of positive and negative rotation, whether blades are staggered, the number of the blades and the length of the blades, so as to obtain the combined data of the mixing parameters and humidifying uniformity under different mixed parameters; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the mixing parameter-humidification uniformity combined data, calibrating each undetermined constant of the humidification uniformity model equation, and obtaining a calibrated humidification uniformity model equation;
The quantitative detection part inputs the mixing parameter variable under the condition to be detected into the calibrated humidification uniformity model equation, and grain humidification uniformity data under the condition are obtained through prediction; and
and the control part is in communication connection with the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part and the quantitative detection part and controls the operation of the model component part, the basic parameter determining part, the water content equation constructing part, the humidification uniformity model equation constructing part and the quantitative detection part.
9. The system for quantitatively detecting the grain humidification uniformity in a spray tempering process according to claim 8, further comprising:
and the input display part is in communication connection with the control part, enables a user to input information for detection and an operation instruction, and performs corresponding display according to the operation instruction.
10. The system for quantitatively detecting the grain humidification uniformity in the spray tempering process according to claim 9, wherein:
wherein, input display part can let the user input the cereal granule that awaits measuring and mix structure size data and the rerum natura data of the machine jar body to can be according to corresponding operating command: displaying a three-dimensional discrete element numerical model of the grain particles and the mixer tank body established by the model component part, displaying the material parameters and the contact parameters determined by the basic parameter determination part in a list form or on a three-dimensional discrete element numerical model diagram, displaying discrete element simulation parameters-grain particle water content combined data and a constructed water content equation obtained by the water content equation construction part, displaying the mixing parameters-humidification uniformity combined data and the constructed humidification uniformity model equation obtained by the humidification uniformity model equation construction part, displaying grain humidification uniformity data and corresponding to-be-measured conditions and mixing parameter variables predicted by the quantitative detection part in a list form or on a three-dimensional discrete element numerical model diagram in a correlation manner, and displaying different grain particles in a color selected by a user according to dry and wet conditions, and the change condition of the grain humidity in the spray tempering process can be dynamically displayed.
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