CN114757072B - Quantitative detection method and system for grain humidification uniformity in spray tempering process - Google Patents
Quantitative detection method and system for grain humidification uniformity in spray tempering process Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000005496 tempering Methods 0.000 title claims abstract description 54
- 239000007921 spray Substances 0.000 title claims abstract description 42
- 239000002245 particle Substances 0.000 claims abstract description 205
- 235000013339 cereals Nutrition 0.000 claims abstract description 110
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 91
- 238000004088 simulation Methods 0.000 claims abstract description 67
- 238000002156 mixing Methods 0.000 claims abstract description 55
- 239000000463 material Substances 0.000 claims abstract description 23
- 239000004464 cereal grain Substances 0.000 claims abstract description 15
- 238000011084 recovery Methods 0.000 claims description 23
- 230000003068 static effect Effects 0.000 claims description 23
- 238000011049 filling Methods 0.000 claims description 13
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- 238000007689 inspection Methods 0.000 description 2
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- 125000000174 L-prolyl group Chemical group [H]N1C([H])([H])C([H])([H])C([H])([H])[C@@]1([H])C(*)=O 0.000 description 1
- 241000209094 Oryza Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 235000021307 Triticum Nutrition 0.000 description 1
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Abstract
The invention provides a quantitative detection method and a quantitative detection system for grain humidification uniformity in a spray tempering process, which are used for quantitatively, accurately and rapidly detecting grain humidification uniformity in the spray tempering process under a complex tank environment and humidification conditions. The quantitative detection method for the humidification uniformity of the grains in the spray tempering process comprises the following steps: step 1, establishing a discrete element numerical model of cereal grains and a mixer tank body; step 2, determining material parameters and contact parameters of the cereal grains and the tank body of the mixer as model basic parameters; step 3, obtaining discrete element simulation parameter-grain particle water content combination data according to the model basic parameters, and calibrating a water content equation by adopting the discrete element simulation parameter-grain particle water content combination data; step 4, inputting combined data of mixing parameters and humidification uniformity, and calibrating a humidification uniformity model equation; and 5, inputting the mixed parameter variable under the condition to be detected into a 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 quantitative detection method and a quantitative detection system for grain humidification uniformity in a spray tempering process.
Background
In the grain production and processing processes of rice, wheat and the like, continuous humidification tempering operation is required to be carried out on the grains, and the process is also widely applied to other grain pretreatment processes. The humidifying and tempering process can enable different grains to reach the water content meeting the processing requirement, thereby improving the product quality. The uneven moisture content of the humidified grains leads to excessive or insufficient local humidification of the grains: when local humidification is uneven, the moisture difference between the inside and the outside of the grain is increased, so that the surface of the grain absorbs more moisture to generate stress cracks; the local soaking environment is formed by the excessive local humidification amount, so that the grain quality is reduced; when the local humidification is insufficient, the grains cannot achieve the purpose of humidification. Therefore, the humidification uniformity is an important index for checking the humidification tempering process performance. In recent years, more and more scholars are focusing on the research of humidification uniformity index detection and evaluation methods.
At present, the common grain humidifying and tempering process mainly comprises countercurrent circulation type and crossflow type. In order to detect the humidification uniformity, a sampling method is generally adopted for statistical inspection, the randomness of the inspection method is great, the difficulty of obtaining samples is great for factors such as different humidification processes, different grain particle properties, different mixer structures and parameters, and the like, and the detection result is inaccurate.
Disclosure of Invention
The invention aims to solve the problems, and aims to provide a quantitative detection method and a quantitative detection system for the humidification uniformity of grains in a spray tempering process, which are applicable to quantitative, accurate and rapid detection of the humidification uniformity of grains in a spray tempering process under a complex tank environment and humidification conditions.
In order to achieve the above object, the present invention adopts the following scheme:
< method >
The invention provides a quantitative detection method for grain humidification uniformity in a spray tempering process, which is characterized by comprising the following steps:
step 1, establishing a three-dimensional discrete element numerical model of the cereal grains and the mixer tank according to structural size data of the cereal grains to be detected and the mixer tank;
step 2, determining material parameters of the cereal particles and the mixer tank body and contact parameters between the particles and the mixer tank body according to physical property data of the cereal particles and the mixer tank body to be detected, 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, can density, can poisson ratio, can shear modulus; the contact parameters include: the recovery coefficient between particles, the static friction coefficient between particles, the dynamic friction coefficient between particles, the recovery coefficient between particles and the inner wall of the tank body, the static friction coefficient between particles and the inner wall of the tank body and the dynamic friction coefficient between particles and the inner wall of the tank body;
step 3, obtaining discrete element simulation parameter-grain particle water content combination data under different water contents according to the model basic parameters, establishing a water content equation representing a mapping relation between the grain wet particle water content and the discrete element simulation parameter, and calibrating each undetermined constant in the water content equation by adopting the discrete element simulation parameter-grain particle water content combination data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, a collision recovery coefficient, an inter-particle static friction coefficient and an inter-particle rolling friction coefficient;
step 4, expressing the water content by adopting discrete element simulation parameters in the water content equation calibrated in the step 3, inputting mixing parameters for simulation of a particle system, wherein the mixing parameters comprise at least one of 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 forward and reverse rotation, whether blades are staggered, the number of blades and the length of the blades, so as to obtain mixing parameter-humidifying uniformity combination data under different mixing parameters; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the combination data of the mixing parameters and the humidification uniformity, calibrating each undetermined constant of the humidification uniformity model equation, and obtaining a calibrated humidification uniformity model equation;
and 5, inputting the mixed parameter variable under the condition to be detected into a calibrated humidification uniformity model equation, and predicting to obtain grain humidification uniformity data under the condition.
Preferably, the quantitative detection method for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: in step 1, modeling, meshing and boundary condition setting are carried out on grain particles and a tank model of the mixer by using three-dimensional modeling software, a model file is exported, and then the model file is imported into discrete element numerical simulation software. The three-dimensional modeling software can be any one of Solidworks, pro/E, CATIA, and the discrete element numerical simulation software is EDEM.
Preferably, the quantitative detection method for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: in step 2, model base parameter settings: the material parameters of the particles and the mixer tank body and the contact parameters between the particles and the mixer tank body are set in discrete element simulation software, and using the JKR model as a particle-particle and particle-particle mixer tank contact model.
Preferably, the quantitative detection method for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: in the step 3, the basic parameters of the model are input into a cohesive force model to obtain the discrete element simulation parameter-grain particle water content combination data under different water contents.
Preferably, the quantitative detection method for grain humidification uniformity in the spray tempering process provided by the invention can also be characterized in that in the step 3, the established water content equation is as follows:
y 1 ＝a 0 +a 1 x 1 +a 2 x 2 +a 3 x 3 +a 4 x 4 ，
wherein y is 1 Is the moisture content of wet particles, x 1 Is the surface energy, x 2 For the collision recovery coefficient, x 3 Is the static friction coefficient between particles, x 4 A is the rolling friction coefficient among particles 0 ～a 4 Is a pending constant.
Preferably, the quantitative detection method for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: in step 4, the humidification tempering numerical simulation: inputting discrete element simulation parameters of surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient into particle system simulation software, wherein each group of discrete element simulation parameters corresponds to a grain particle water content; adding the same quantity of dry and wet grains with different water contents under the condition of certain mixing parameters to carry out a humidifying tempering numerical simulation test, and respectively calibrating the dry and wet grains with the same grain diameter and the same attribute into different colors in an initial state; and quantitatively analyzing particle distribution data in simulation software by adopting a separation index, and quantitatively characterizing humidification uniformity of grains.
Preferably, the quantitative detection method for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: in step 4, the established humidification uniformity model equation is:
z＝b 0 +b 1 y 1 +b 2 y 2 y 3 +b 3 y 4 +b 4 y 5 +b 5 y 6 y 7 y 8 +b 6 y 9 ，
wherein z is humidification uniformity, y 1 Is the moisture content of wet particles, y 2 Is of particle size, y 3 For filling rate, y 4 Is the rotation speed, y 5 For mixing time, y 6 Taking 1 in forward and reverse rotation, taking-1 in reverse rotation, y 7 1 is taken if the blades are staggered, 1 is taken if not, and y is taken as-1 8 For the number of blades, y 9 For blade length, b 0 ～b 6 Is a pending constant.
< System >
Furthermore, the invention also provides a quantitative detection system for grain humidification uniformity in a spray tempering process, which can automatically realize the method, and is characterized by comprising the following steps:
the model component part is used for establishing a three-dimensional discrete element numerical model of the cereal grains and the mixer tank according to structural size data of the cereal grains to be detected and the mixer tank;
a basic parameter determining part for determining material parameters of the grains and the tank body of the mixer and contact parameters between the grains and the tank body of the mixer and between the grains and the tank body of the mixer according to physical property data of the grains and the tank body of the mixer to be detected, 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, can density, can poisson ratio, can shear modulus; the contact parameters include: the recovery coefficient between particles, the static friction coefficient between particles, the dynamic friction coefficient between particles, the recovery coefficient between particles and the inner wall of the tank body, the static friction coefficient between particles and the inner wall of the tank body and the dynamic friction coefficient between particles and the inner wall of the tank body;
the water content equation construction part is used for obtaining discrete element simulation parameter-grain particle water content combination data under different water contents according to the model basic parameters, establishing a water content equation representing the mapping relation between the grain wet particle water content and the discrete element simulation parameter, and calibrating each undetermined constant in the water content equation by adopting the discrete element simulation parameter-grain particle water content combination data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, a collision recovery coefficient, an inter-particle static friction coefficient and an inter-particle rolling friction coefficient;
the humidifying uniformity model equation construction part adopts discrete element simulation parameters in the calibrated water content equation to represent the water content, inputs mixing parameters to carry out particle system simulation, wherein 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 forward and reverse rotation, staggered blades, the number of the blades and the length of the blades, and the mixing parameters-humidifying uniformity combined data under different mixing parameters are obtained; establishing a humidification uniformity model equation representing a mapping relation between the mixed parameters and the humidification uniformity, inputting mixed parameter-humidification uniformity combination 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 mixed parameter variable under the condition to be detected into a calibrated humidification uniformity model equation, and predicts to obtain grain humidification uniformity data under the condition; 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 quantitative detection system for the humidification uniformity of the grains in the spray tempering process provided by the invention can further comprise: and an input display part which is communicated with the control part and allows a user to input detection information and operation instructions and correspondingly display the detection information and the operation instructions according to the operation instructions.
Preferably, the quantitative detection system for the humidification uniformity of the grains in the spray tempering process provided by the invention can be further characterized by comprising the following steps: the input display part allows a user to input structural size data and physical property data of the cereal grains to be detected and the tank body of the mixer, and can be used for controlling the mixing machine according to corresponding operation instructions: the grain particles established by the model component part and the three-dimensional discrete element numerical model of the tank body of the mixer are displayed, the material parameters and the contact parameters determined by the basic parameter determining part are displayed in a list form or on a three-dimensional discrete element numerical model diagram, the discrete element simulation parameter-grain particle water content combination data and the constructed water content equation are obtained by the water content equation constructing part, the mixed parameter-humidification uniformity combination data and the constructed humidification uniformity model equation obtained by the humidification uniformity model equation constructing part are displayed, the grain humidification uniformity data predicted by the quantitative detecting part and the corresponding conditions to be detected and the mixed parameter variables are displayed in a list form or on a three-dimensional discrete element numerical model diagram, different grain particles are displayed in different colors selected by a user according to the dry and wet conditions, and the grain particle humidity change condition in the spray tempering process can be dynamically displayed.
Effects and effects of the invention
The quantitative detection method and the quantitative detection system for the humidification uniformity of the grains in the spray tempering process can be suitable for quantitative detection of the humidification uniformity of the grains in the spray tempering process under complex tank environments such as different humidification processes, different grain particle properties, different mixer structures and parameters, and the like, can sample and detect the humidification uniformity at any time, are quite simple in measurement process, are visual and accurate in measurement result, and do not involve damage of samples in the measurement process. Has very important significance and value for regulating and controlling the uniformity of humidification tempering, improving the quality of grains and optimizing the design of mixing parameters of humidification tempering equipment.
Drawings
FIG. 1 is a flow chart of a quantitative detection method for grain humidification uniformity in a spray tempering process according to an embodiment of the invention;
FIG. 2 is a numerical model of brown rice granules according to the first embodiment of the present invention;
FIG. 3 is a numerical model of a tank according to a first embodiment of the present invention;
FIG. 4 is a graph showing the mixing state of particles at the end of the simulation in accordance with the first embodiment of the present invention;
FIG. 5 is a graph showing the degree of mixing of particles according to the first embodiment of the present invention;
FIG. 6 is a numerical model of brown rice granules according to the second embodiment of the present invention;
FIG. 7 is a graph showing the mixing state of particles at the end of the simulation in accordance with 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
Specific embodiments of the method and system for quantitatively detecting the humidification uniformity of grains in a spray tempering process according to the present invention are described in detail below with reference to the accompanying drawings.
Example 1
As shown in fig. 1, the quantitative detection method for grain humidification uniformity in the spray tempering process provided in the first embodiment specifically includes:
modeling, meshing and boundary condition setting are carried out on the particle and mixer model by using SolidWorks2019 software, a model file is exported, and then the model file is imported into EDEM discrete element simulation software. The brown rice is taken as a particle prototype, and as shown in fig. 2, the established particle numerical model is an elliptical model with a long axis of 6mm and a short axis of 3.125 mm. The numerical model of the mixer tank is shown in fig. 3. Simulation parameters such as the 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 parameters required for simulation
The JKR cohesion model was used as a particle-to-particle, particle-to-mixer contact model. Calibrating the moisture content of the wet particles by using a JKR model, firstly carrying out a stacking test on 37 groups of brown rice with the total moisture content of 12% -30% and the interval of 0.5%, and determining the real stacking angle corresponding to the moisture content of the brown rice wet particles; and taking the real stacking angle as an evaluation index to obtain 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 wet particle water content. 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 significant discrete element simulation parameters by taking the stacking angle as an intermediate variable, wherein the correlation equation is as follows:
y 1 ＝19.8+3.62x 1 -1.75x 2 +0.56x 3 +0.25x 4 ，
wherein y is 1 Is the moisture content of wet particles, x 1 Is the surface energy, x 2 For the collision recovery coefficient, x 3 Is the static friction coefficient between particles, x 4 Is the rolling friction coefficient between particles. R of wet particle moisture content and discrete element simulation parameters 2 0.81.
And then under the discrete element simulation environment, inputting 2 groups of brown rice particles with different water contents (in EDEM simulation software, the calibrated discrete element simulation parameters are combined to serve as input parameters, and the water contents of the brown rice particles are represented by the input parameters), wherein the water contents of the 2 groups of brown rice particles are 14.5% and 15.5% respectively. According to the method, a humidification simulation test is carried out. The properties and the quantity of the 2 groups of brown rice particles are identical. The mixing parameters were set as follows: the particle size of the particles is 3.8mm; the rotating speed is 20r/min, 30r/min and 40r/min; the filling rate is 40.2%, 50.5% and 60.8%; mixing time 45S; the same rotation and the staggered blades are adopted, the number of the blades is 3, and the lengths of the blades are 165mm, 175mm and 185mm. And respectively calibrating dry and wet particles with the same particle size and the same attribute into 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 test, grain data distribution data as shown in fig. 4 was derived from the simulation software. According to the grain distribution data derived from the simulation software, grain humidification uniformity is quantitatively characterized by taking a separation index as an index, wherein the separation index is shown in fig. 5.
The establishment of the mixing parameter and humidification uniformity model equation is as follows:
z＝0.39-0.15y 1 +0.027y 2 y 3 +0.0013y 4 -0.00005y 5 -0.0073y 6 y 7 y 8 +0.0026y 9 ，
wherein z is the humidification uniformity (separation index characterizes the humidification uniformity), y 1 Is the moisture content of wet particles, y 2 Is of particle size, y 3 For filling rate, y 4 Is the rotation speed, y 5 For mixing time, y 6 Taking 1 in forward and reverse rotation, taking-1 in reverse rotation, y 7 1 is taken if the blades are staggered, and-1 and y are taken if not 8 For the number of blades, y 9 Is the blade length.
And predicting according to the humidification uniformity model equation to obtain: the moisture content of the particles is 0.15, the particle sizes of the particles are 3.8mm, the rotating speed is 30r/min, the filling rate is 48.6%, the mixing time is 48S, the blade length is 180mm, the rotation is reversed, the blades are staggered, and the humidifying uniformity is 0.78 under the mixing condition of 4 blades. The result of the real humidifying uniformity of the humidifying 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 quantitative detection method for the humidification uniformity of grains in the spray tempering process provided in the second embodiment specifically includes:
modeling, meshing and boundary condition setting are carried out on the particle and mixer model by using SolidWorks2019 software, a model file is exported, and then the model file is imported into EDEM discrete element simulation software. The brown rice was used as a particle prototype, and the numerical particle model was an elliptical model with a major axis of 7.063mm and a minor axis of 2.750mm (FIG. 6). The numerical model of the mixer tank is shown in fig. 3. The material properties of the particles 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. Calibrating the moisture content of the wet particles by using a JKR model, firstly carrying out a stacking test on 37 groups of brown rice with the total moisture content of 12% -30% and the interval of 0.5%, and determining the real stacking angle corresponding to the moisture content of the brown rice wet particles; and taking the real stacking angle as an evaluation index to obtain 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 wet particle water content. The correlation equation between the moisture content of the brown rice wet particles and the significant discrete element simulation parameters is established by taking the stacking angle as an intermediate variable, and is as follows:
y 1 ＝23.5-1.86x 1 +0.93x 2 -3.58x 3 +2.93x 4 ，
wherein y is 1 Is the moisture content of wet particles, x 1 Is the surface energy, x 2 For the collision recovery coefficient, x 3 Is the static friction coefficient between particles, x 4 Is the rolling friction coefficient between particles. R of wet particle moisture content and discrete element simulation parameters 2 0.93.
And then under the discrete element simulation environment, inputting 2 groups of brown rice particles with different water contents (in EDEM simulation software, the calibrated discrete element simulation parameters are combined to serve as input parameters, and the water contents of the brown rice particles are represented by the input parameters), wherein the water contents of the 2 groups of brown rice particles are 23.5% and 25.5% respectively. According to the method, a humidification simulation test is carried out. The properties and the quantity of the 2 groups of brown rice particles are identical. The mixing parameters were set as follows: the particle size of the particles is 4.5mm; the rotating speed is 20r/min, 30r/min and 40r/min; the filling rate is 41.1%, 52.9% and 61.8%; mixing time 45S; reverse rotation, staggered blades, 4 blades, and 170mm, 180mm and 190mm blade length. And respectively calibrating dry and wet particles with the same particle size and the same attribute into 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 test, grain data distribution data as shown in fig. 7 was derived from the simulation software. According to the grain distribution data derived from the simulation software, grain humidification uniformity is quantitatively characterized by taking a separation index as an index, wherein the separation index is shown in fig. 8.
The establishment of the mixing parameter and humidification uniformity model equation is as follows:
z＝0.47+0.16y 1 +0.03y 2 y 3 -0.001y 4 -0.00006y 5 -0.006y 6 y 7 y 8 +0.0019y 9 ，
wherein z is the humidification uniformity (separation index characterizes the humidification uniformity), y 1 Is the moisture content of wet particles, y 2 Is of particle size, y 3 For filling rate, y 4 Is the rotation speed, y 5 For mixing time, y 6 Taking 1 in forward and reverse rotation, taking-1 in reverse rotation, y 7 1 is taken if the blades are staggered, and-1 and y are taken if not 8 For the number of blades, y 9 Is the blade length.
And predicting according to the humidification uniformity model equation to obtain: the moisture content of the particles is 0.245, the particle sizes of the particles are 4.5mm, the rotating speed is 40r/min, the filling rate is 62.6%, the mixing time is 45S, the blade length is 175mm, the blades are rotated forwards, staggered, and the humidifying uniformity is 0.86 under the mixing condition of 3 blades. The result of the real humidifying uniformity of the humidifying 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 process under complex tank environments such as different humidification processes, different grain particle properties, different mixer structures and parameters and the like. The measurement data and the measurement result show that the mixing parameters and the humidity uniformity correlation under the discrete element simulation environment can be used for rapidly, simply and accurately detecting the humidity uniformity of the grains, and a rapid and accurate detection method is provided for detecting the humidity uniformity of the grains in the spray tempering process.
Further, the embodiment also provides a quantitative detection system for grain humidification uniformity in a spray tempering process, which can automatically realize the method, and 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 cereal grains and the mixer tank body according to the structural size data of the cereal grains to be detected and the mixer tank body.
The basic parameter determining part determines material parameters of the cereal particles and the mixer tank body and contact parameters between the particles and the mixer tank body according to physical property data of the cereal particles to be detected and the mixer 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, can density, can poisson ratio, can shear modulus; the contact parameters include: the recovery coefficient between particles, the static friction coefficient between particles, the dynamic friction coefficient between particles, the recovery coefficient between particles and the inner wall of the tank body, the static friction coefficient between particles and the inner wall of the tank body and the dynamic friction coefficient between particles and the inner wall of the tank body.
The water content equation construction part obtains discrete element simulation parameter-grain particle water content combination data under different water contents according to the model basic parameters, establishes a water content equation representing the mapping relation between the grain wet particle water content and the discrete element simulation parameter, and adopts the discrete element simulation parameter-grain particle water content combination data to calibrate each undetermined constant in the water content equation 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 humidifying uniformity model equation construction part adopts discrete element simulation parameters in the calibrated water content equation to represent the water content, inputs mixing parameters to carry out particle system simulation, wherein 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 forward and reverse rotation, whether blades are staggered or not, the number of blades and the length of the blades, and the combined data of mixing parameters-humidifying uniformity under different mixing parameters is obtained; and establishing a humidification uniformity model equation representing a mapping relation between the mixed parameters and the humidification uniformity, inputting mixed parameter-humidification uniformity combination 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 mixed parameter variable under the condition to be detected into a calibrated humidification uniformity model equation, and predicts to obtain grain humidification uniformity data under the condition.
The input display unit is used for enabling a user to input detection information and operation instructions and correspondingly display the detection information and the operation instructions according to the operation instructions. For example, the input display portion can enable a user to input structural dimension data and physical property data of cereal grains to be tested and the tank body of the mixer, and can be used for controlling the mixing machine according to corresponding operation instructions: the grain particles established by the model component part and the three-dimensional discrete element numerical model of the tank body of the mixer are displayed, the material parameters and the contact parameters determined by the basic parameter determining part are displayed in a list form or on a three-dimensional discrete element numerical model diagram, the discrete element simulation parameter-grain particle water content combination data and the constructed water content equation are obtained by the water content equation constructing part, the mixed parameter-humidification uniformity combination data and the constructed humidification uniformity model equation obtained by the humidification uniformity model equation constructing part are displayed, the grain humidification uniformity data predicted by the quantitative detecting part and the corresponding conditions to be detected and the mixed parameter variables are displayed in a list form or on a three-dimensional discrete element numerical model diagram, different grain particles are displayed in different colors selected by a user according to the dry and wet conditions, and the grain particle humidity change condition in the spray tempering process can be dynamically displayed.
The control part is communicated 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, 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, the quantitative detection part and the input display part.
The above embodiments are merely illustrative of the technical solutions of the present invention. The quantitative detection method and system for the humidification uniformity of the grains in the spray tempering process according to the invention are not limited to the above embodiments, but the scope of the invention is defined by the claims. Any modifications, additions or equivalent substitutions made by those skilled in the art based on this embodiment are within the scope of the invention as claimed in the claims.
Claims (10)
1. The quantitative detection method for the humidification 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 cereal grains and the mixer tank according to structural size data of the cereal grains to be detected and the mixer tank;
step 2, determining material parameters of the cereal particles and the mixer tank body and contact parameters between the particles and the mixer tank body according to physical property data of the cereal particles and the mixer tank body to be detected, 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, can density, can poisson ratio, can shear modulus; the contact parameters include: the recovery coefficient between particles, the static friction coefficient between particles, the dynamic friction coefficient between particles, the recovery coefficient between particles and the inner wall of the tank body, the static friction coefficient between particles and the inner wall of the tank body and the dynamic friction coefficient between particles and the inner wall of the tank body;
step 3, discrete element simulation parameter-grain particle water content combination 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 parameter is established, and each undetermined constant in the water content equation is calibrated by adopting the discrete element simulation parameter-grain particle water content combination data, so that a calibrated water content equation is obtained; the discrete element simulation parameters comprise surface energy, a collision recovery coefficient, an inter-particle static friction coefficient and an inter-particle rolling friction coefficient;
step 4, expressing the water content by adopting discrete element simulation parameters in a calibrated water content equation, inputting mixing parameters to perform particle system simulation, wherein the mixing parameters comprise at least one of 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 forward and reverse rotation, whether blades are staggered, the number of blades and the length of the blades, so as to obtain mixing parameter-humidifying uniformity combination data under different mixing parameters; establishing a humidification uniformity model equation representing a mapping relation between the mixing parameters and the humidification uniformity, inputting the combination data of the mixing parameters and the humidification uniformity, calibrating each undetermined constant of the humidification uniformity model equation, and obtaining a calibrated humidification uniformity model equation;
and 5, inputting the mixed parameter variable under the condition to be detected into a calibrated humidification uniformity model equation, and predicting to obtain grain humidification uniformity data under the condition.
2. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
in step 1, a grain particle and a mixer tank model are modeled, meshed and boundary conditions are set by using three-dimensional modeling software, a model file is exported, and then the model file is imported into discrete element numerical simulation software.
3. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
wherein, in step 2, the model basic parameter is set: the material parameters of the particles and the mixer tank body and the contact parameters between the particles and the mixer tank body are set in discrete element simulation software, and using the JKR model as a particle-particle and particle-particle mixer tank contact model.
4. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
in step 3, the basic parameters of the model are input into a cohesive force model to obtain the discrete element simulation parameter-grain particle water content combination data under different water contents.
5. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
in the step 3, the established water content equation is:
y 1 ＝a 0 +a 1 x 1 +a 2 x 2 +a 3 x 3 +a 4 x 4 ，
wherein y is 1 Is the moisture content of wet particles, x 1 Is the surface energy, x 2 For the collision recovery coefficient, x 3 Is the static friction coefficient between particles, x 4 A is the rolling friction coefficient among particles 0 ～a 4 Is a pending constant.
6. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
in the step 4, the humidification tempering numerical simulation is performed: inputting discrete element simulation parameters of surface energy, collision recovery coefficient, inter-particle static friction coefficient and inter-particle rolling friction coefficient into particle system simulation software, wherein each group of discrete element simulation parameters corresponds to a grain particle water content; adding the same quantity of dry and wet grains with different water contents under the condition of certain mixing parameters to carry out a humidifying tempering numerical simulation test, and respectively calibrating the dry and wet grains with the same grain diameter and the same attribute into different colors; and quantitatively analyzing particle distribution data in simulation software by adopting a separation index, and quantitatively characterizing humidification uniformity of grains.
7. The quantitative detection method for humidification uniformity of grains in a spray tempering process according to claim 1, wherein the quantitative detection method is characterized by comprising the following steps:
in step 4, the established humidification uniformity model equation is:
z＝b 0 +b 1 y 1 +b 2 y 2 y 3 +b 3 y 4 +b 4 y 5 +b 5 y 6 y 7 y 8 +b 6 y 9 ，
wherein z is humidification uniformity, y 1 Is the moisture content of wet particles, y 2 Is of particle size, y 3 For filling rate, y 4 Is the rotation speed, y 5 For mixing time, y 6 Taking 1 in forward and reverse rotation, taking-1 in reverse rotation, y 7 1 is taken if the blades are staggered, and-1 and y are taken if not 8 For the number of blades, y 9 For blade length, b 0 ～b 6 Is a pending constant.
8. The quantitative detection system for humidification uniformity of grain in a spray tempering process according to any one of claims 1 to 7, wherein the quantitative detection method for humidification uniformity of grain in a spray tempering process is automatically used for detection, and is characterized by comprising:
the model component part is used for establishing a three-dimensional discrete element numerical model of the cereal grains and the mixer tank according to structural size data of the cereal grains to be detected and the mixer tank;
a basic parameter determining part for determining material parameters of the grains and the tank body of the mixer and contact parameters between the grains and the tank body of the mixer and between the grains and the tank body of the mixer according to physical property data of the grains and the tank body of the mixer to be detected, 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, can density, can poisson ratio, can shear modulus; the contact parameters include: the recovery coefficient between particles, the static friction coefficient between particles, the dynamic friction coefficient between particles, the recovery coefficient between particles and the inner wall of the tank body, the static friction coefficient between particles and the inner wall of the tank body and the dynamic friction coefficient between particles and the inner wall of the tank body;
the water content equation construction part is used for obtaining discrete element simulation parameter-grain particle water content combination data under different water contents according to the model basic parameters, establishing a water content equation representing the mapping relation between the grain wet particle water content and the discrete element simulation parameter, and calibrating each undetermined constant in the water content equation by adopting the discrete element simulation parameter-grain particle water content combination data to obtain a calibrated water content equation; the discrete element simulation parameters comprise surface energy, a collision recovery coefficient, an inter-particle static friction coefficient and an inter-particle rolling friction coefficient;
the humidifying uniformity model equation construction part adopts discrete element simulation parameters in the calibrated water content equation to represent the water content, inputs mixing parameters to carry out particle system simulation, wherein 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 forward and reverse rotation, staggered blades, the number of the blades and the length of the blades, and the mixing parameters-humidifying uniformity combined data under different mixing parameters are obtained; establishing a humidification uniformity model equation representing a mapping relation between the mixed parameters and the humidification uniformity, inputting mixed parameter-humidification uniformity combination 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 mixed parameter variable under the condition to be detected into a calibrated humidification uniformity model equation, and predicts to obtain grain humidification uniformity data under the condition; and
and the control part is communicated 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 quantitative detection system for humidification uniformity of grain in a spray tempering process according to claim 8, further comprising:
and the input display part is communicated with the control part, and allows a user to input detection information and operation instructions and correspondingly display the detection information and the operation instructions according to the operation instructions.
10. The quantitative detection system for humidification uniformity of grain in a spray tempering process according to claim 9, wherein:
the input display part can enable a user to input structural size data and physical property data of cereal grains to be detected and the tank body of the mixer, and can be used for controlling the mixing machine according to corresponding operation instructions: the three-dimensional discrete element numerical model of the grain particles and the mixer tank body established by the model component part is displayed, the material parameters and the contact parameters determined by the basic parameter determining part are displayed in a list form or on a three-dimensional discrete element numerical model diagram, discrete element simulation parameter-grain particle water content combination data and a constructed water content equation are obtained by the water content equation constructing part, the mixed parameter-humidification uniformity combination data and the constructed humidification uniformity model equation obtained by the humidification uniformity model equation constructing part are displayed, the grain humidification uniformity data predicted by the quantitative detecting part and corresponding conditions to be detected and mixed parameter variables are displayed in a list form or on a three-dimensional discrete element numerical model diagram, different grain particles are displayed in different colors 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.
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