CN113702605B - Method for measuring migration rule of dry moisture of grains in warehouse - Google Patents
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Abstract
The method for measuring the migration rule of the dry moisture of the grains in the bin comprises a simulation bin, wherein the simulation bin comprises a cylindrical bin body, and the top of the bin body is connected with a conical bin top in a sealing way; the bottom of the inner side of the simulation bin is provided with a bottom plate for placing grains, the bottom plate is of a net structure which is beneficial to ventilation, the bottom plate and the bottom of the bin body form an air distribution chamber, one side of the air distribution chamber is provided with an air inlet, the other side of the air distribution chamber is provided with an air outlet, and the air inlet is communicated with an air supply device through a pipeline; the middle part of the bin body is provided with a temperature and humidity detection cable, and each temperature and humidity detection cable is provided with a temperature and humidity sensor at a certain distance; and a plurality of sampling points are uniformly arranged at the plane positions corresponding to the temperature and humidity sensors. According to the invention, the drying process of grains with different moisture contents under different ventilation conditions is simulated, the moisture migration rule of the grains in the bin drying process is explored, the grain drying dynamics model is established, and necessary data support is provided for the bin drying of high-moisture grains.
Description
Technical Field
The invention belongs to the technical field of grain drying, and relates to a method for measuring a grain in-house drying moisture migration rule.
Background
As grain which is not stored, the quality of the grain is easily deteriorated due to the influence of factors such as temperature, humidity, moisture content of the grain, pests and the like in the processes of harvesting, drying and storing the grain. In order to stabilize the quality of the grains, the harvested high-moisture grains are subjected to precipitation drying treatment, and the grains are stored in a warehouse after the moisture content of the grains is dried to safe storage moisture. At present, due to the imbalance of economic level and technical condition in different areas of China, the drying of high-moisture grains is still three technologies of a manual airing method, a dryer drying method and an in-house drying method. In the process of storing harvested grains in a silo with a mechanical ventilation system, natural air or heated air is used as a drying medium, and grain moisture is reduced to be within a standard through air displacement inside and outside a grain pile in a short time, and the grain is stored in the silo. The main purpose is to carry out mechanical ventilation treatment on the high-moisture grains, so that the grains can reach the safe storage standard moisture content before entering storage, the storage period of the grains is prolonged, and the storage safety of the grains is ensured. Compared with the drying of a dryer, the method has the advantages of low energy consumption, small influence on the quality of grain and food, and the like, and Wu Xiaoyu and other researches find that after the grain moisture content is reduced to a range of 13.4-14.9% by using the bin drying technology, the grain temperature is free from abnormal phenomenon, the grain quality is free from obvious change, and compared with the drying of the dryer, the method has lower running cost, and can better ensure the grain quality on the basis of completing precipitation. At present, related researches focus on the quality change rule of the grain drying process, such as Meas and the like, and research on the influence of high-temperature drying at 50 ℃ on the grain quality shows that the thinner the grain thickness is, the higher the turning frequency is, the slower the drying rate is, the smaller the air flow rate is, and the higher the whole polished rice rate of the grain is. In order to ensure that the moisture distribution in the grain pile drying process is uniform, huang Aiguo and the like adopt a layering bin drying mode, so that the average moisture of the grain pile is reduced from 16.9% to 13.7%, and the moisture layering phenomenon can be effectively improved. There is little research on the rule of moisture migration of grain piles in the whole grain drying process.
The method can timely dry grains just after harvest, ensures the quality safety of the grain drying process, measures the drying process of grains with different moisture contents under different ventilation conditions, explores the moisture migration rule of the grains in the bin drying process, and provides necessary data support for the bin drying of high-moisture grains.
Disclosure of Invention
The invention aims to provide a method for measuring the migration rule of dry moisture in a grain bin.
To achieve the above and other related objects, the present invention provides the following technical solutions: the measuring method of the grain dry moisture migration law comprises a simulation bin, wherein the simulation bin comprises a cylindrical bin body, and the top of the bin body is connected with a conical bin top in a sealing way; the bottom of the inner side of the simulation bin is provided with a bottom plate for placing grains, the bottom plate is uniformly provided with a plurality of through holes, the bottom plate and the bottom of the bin body form an air distribution chamber, one side of the air distribution chamber is provided with an air inlet, the other side of the air distribution chamber is provided with an air outlet, and the air inlet is communicated with an air supply device through a pipeline; the middle part of the bin body is provided with a temperature and humidity detection cable, and each temperature and humidity detection cable is provided with a temperature and humidity sensor at a certain distance; a plurality of sampling points are uniformly arranged at the plane positions corresponding to the temperature and humidity sensors;
the measuring method comprises the following steps:
(1) Determining total ventilation
The total ventilation quantity refers to the total air volume passing through the ventilation system in unit time, and the calculation formula is as follows:
Q total (S) =q×v×r, formula (1);
Q total (S) Total ventilation, m 3 /h; q-unit ventilation, m 3 /(h·t)；
V-volume of grain pile, m 3 The method comprises the steps of carrying out a first treatment on the surface of the r-grain volume weight, t/m 3 ；
(2) Initial conditions:
setting the ambient temperature to 15 ℃ and the relative humidity to be 60%, pouring grains into a simulation bin to the position of a 1m scale mark in the bin, sampling every 1d at sampling points for each batch of grains with the total weight of 300kg, and measuring the moisture content of the grains at the sampling points until at least one layer of safe storage moisture with the moisture content as low as 14% exists in a grain pile;
(3) The measuring method comprises the following steps:
1. the method for calculating the drying rate of the grain is as follows:
wherein: v i -drying rate of cereal at moment i/(%/d); omega i -moisture mass fraction of cereal at moment i/%; omega t -grain moisture mass fraction/% -at time t.
2. Calculation of the Water percentage
The method for calculating the moisture ratio of the grains at the time t of bin drying is as follows:
wherein, the grain water ratio at the moment of MR-t; m is M t -drying the moisture content,%;
M 0 -initial moisture content of cereal,%; m is M e -grain equilibrium moisture content,%;
3. grain equilibrium moisture M e The calculation method is as follows:
wherein RH—relative humidity,%; t (T) a -absolute temperature of the grain stack, K;
4. the effective moisture diffusion coefficient calculation method is as follows:
taking the logarithm of equation (5) on both sides, and letting n=1, equation (6) can be obtained:
wherein, the grain water ratio at the moment of MR-t; d (D) eff Effective moisture diffusion coefficient, m 2 /d；
t-drying time, d; l is the general height, m, of the grain layer thickness of the grains;
as can be seen from the formula (6), the effective water diffusion coefficient D of the grain layer can be calculated by drawing a curve between the lnMR and the time t and linearly fitting the curve according to the obtained slope eff ；
5. Mathematical model fitness evaluation equation
Data fitting is carried out on grain in-situ drying through 8 drying mathematical models, and the correlation coefficient R of fitting results is used 2 And judging the model most suitable for the change of the moisture content of each layer of grain pile in the bin drying and ventilation process from 8 mathematical models by using the root error of the square root; the calculation formula is as follows:
wherein MR is Actual measurement value -a certain data point test measured moisture ratio; MR (magnetic resonance) Analog value -predicting the resulting moisture ratio from the mathematical model for a certain data point; n—number of test data points; the fitting degree between the 8 dry mathematical models and the measured value can be based on the correlation coefficient R 2 And Root Mean Square Error (RMSE) when the correlation coefficient R 2 The closer to 1, the smaller the root mean square error RMSE value, which illustrates the better fit of the equation.
The cereal is one of cereal, wheat and corn kernel.
Due to the application of the technical scheme, compared with the prior art, the invention has the advantages that:
according to the method, the drying process of grains with different moisture contents under different ventilation conditions is simulated, the moisture migration rule of the grains in the bin drying process is explored, a grain drying dynamics model is established, and necessary data support is provided for the bin drying of high-moisture grains.
Drawings
Fig. 1 is a schematic perspective view of a simulation cartridge.
FIG. 2 is a schematic cross-sectional view of a simulated bin.
Fig. 3 is a schematic diagram of a sample point layout.
FIG. 4 graph of moisture change for each layer of a grain pile (A: 104m 3 /h；B：92m 3 /h；C：80m 3 /h)。
FIG. 5 variation of moisture drying rate for each layer of cereal grain (FIG. 5A:104 m) 3 /h；B：92m 3 /h；C：80m 3 /h)。
FIG. 6 variation of the moisture ratio of the layers of the stacks under different aeration conditions (A: 104m 3 /h；B：92m 3 /h；C：80m 3 /h)。
FIG. 7lnMR/t fitting graph (A: 104m 3 /h；B：92m 3 /h；C：80m 3/ h)。
FIG. 8104m 3 And (3) fitting a model of the layer number of 15cm and 75cm grains under the ventilation condition.
Detailed Description
Further advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure of the present specification, which follows by reference to the detailed description.
Please refer to fig. 1-5. It should be understood that the structures, proportions, sizes, etc. shown in the drawings are shown only in the drawings and should not be taken as limiting the invention to those structures, proportions, or otherwise, used by those skilled in the art, which may be modified or otherwise, used in the practice of the invention, without the attendant advantages of the same general knowledge and understanding, and without the limitation to the specific features of the present invention. The following examples are provided for a better understanding of the present invention, but are not intended to limit the present invention. The experimental methods in the following examples are conventional methods unless otherwise specified. The experimental materials used in the examples described below were obtained from conventional biochemical reagent shops unless otherwise specified.
Examples: method for measuring migration rule of dry moisture of grains in warehouse
1 materials and methods
1.1 materials and apparatus
Japonica rice produced in 2019: south japonica 5055; the production place: anhui Lujiang; the initial moisture content was 22.60%.
Simulation warehouse and grain condition measurement and control extension set, compound fertilizer Hongen electromechanical technology limited company; CZR small centrifugal fan, shanghai high-workers limited; testo410-2 multifunctional impeller anemometer: deck instruments International trade (Shanghai) Limited; 1m Shan Kongqian sampler; GZX-GF 101-3BS electrothermal constant temperature blast drying oven, shanghai, medical instruments Inc.
As shown in FIGS. 1 and 2, the simulated bin has a diameter of 800mm, a height of 1300mm and a full bin capacity of about 0.5m 3 .1 temperature and humidity detection cable is positioned at the center of the grain pile, and one temperature and humidity sensor is arranged at intervals of 150mm from the grain surfaceSix points are arranged, the sampling height corresponds to the sampling position, and the sampling position is shown in figure 2; in order to ensure that the samples are representative, the grain surface is equally divided into three parts by taking the temperature and humidity cable as the center, as shown in fig. 2, each sampling point is 150mm away from the grain surface, then the next longitudinal sampling point is 150mm away, and each layer of grain surface is a mixed sample of 3 sampling points.
1.2 Experimental methods
1.2.1 determination of ventilation
(1) Determination of unit ventilation
The unit ventilation refers to the ventilation volume per ton of grain per hour. In this test, the test was carried out in batches, and the initial moisture content measured before the storage of the three groups of test grains was measured slightly different, but the moisture content of the grains was in the range of 21 to 23%, and the grain thickness was about 1m, so that the lowest unit ventilation rate of the grain pile was determined to be 192m 3/(h.t) according to the description in "grain drying technology brief (continuous twelve) [20 ].
(2) Determination of total ventilation
The total ventilation quantity refers to the total air volume passing through the ventilation system in unit time, and the calculation formula is as follows:
Q total (S) =q×v×r, formula (1);
Q total (S) Total ventilation, m 3 /h; q-unit ventilation, m 3 /(h·t)；
V-volume of grain pile, m 3 The method comprises the steps of carrying out a first treatment on the surface of the r-grain volume weight, t/m 3 。
As described by the data, the loss rate of ventilation rate in the previous experiment is about 25-30%, so that the minimum total ventilation rate of the grain pile is about 80m 3 And/h. Three sets of ventilation design considerations select minimum ventilation to fan maximum ventilation, namely: 80. 92, 104m 3 /h。
(3) Determination of fans
The model of the CZR small centrifugal fan required by the test is determined according to the minimum ventilation quantity, and the basic parameters are as follows: 100 W, 220V, 0.46A current, 240Pa wind pressure, 2800r/min rotation speed and 2m ventilation 3 Per min, the maximum ventilation rate of the fan is 104m measured by an anemometer 3 /hThe ventilation quantity is larger than the minimum ventilation quantity required by the test, and meets the requirement of the test.
1.2.2 test methods
According to the quality change rule test, setting the ambient temperature to 15 ℃ and the humidity to 60%, pouring grains into a simulation bin to the position of a 1m scale mark in the bin, sampling every 1d according to the set sampling points every 1d, and measuring the moisture content of grains at each sampling point until at least one layer of safe storage moisture with the moisture content as low as 14% exists in a grain pile.
Parameters such as initial moisture content of the test raw material grains are shown in table 1:
table 1 initial conditions of test grains under three ventilation conditions
| Ventilation quantity (m) 3 /h) | Initial moisture content (%) | Grain pile temperature (DEG C) | Grain bulk humidity (%) |
| 104 | 22.60 | 11 | 58 |
| 92 | 21.24 | 8 | 60 |
| 80 | 22.17 | 12 | 65 |
1.2.3 measurement method
(1) Moisture determination: reference is made to GB/T5497-1985 for testing moisture determination methods for foodstuffs and oils;
(2) And (3) calculating a drying rate: the drying rate of the cereal can be determined using the method of Falade calculation as follows:
wherein: v i -drying rate of cereal at moment i/(%/d); omega i -moisture mass fraction of cereal at moment i/%; omega t -grain moisture mass fraction/% -at time t.
2. Calculation of the Water percentage
The moisture ratio of the grain at time t of bin drying can be calculated from formula (3):
wherein, the grain water ratio at the moment of MR-t; m is M t -drying the moisture content,%;
M 0 -initial moisture content of cereal,%; m is M e -grain equilibrium moisture content,%;
3. and grain equilibrium moisture Me can be calculated according to the modified Henderson equation equilibrium moisture model as formula (4):
wherein RH—relative humidity,%; t (T) a -absolute temperature of the grain stack, K;
4. the effective moisture diffusion coefficient calculation method is as follows:
the effective moisture diffusion coefficient can be calculated according to the formula (5) and the formula (6):
taking the logarithm of equation (5) on both sides, and letting n=1, equation (6) can be obtained:
wherein, the grain water ratio at the moment of MR-t; d (D) eff Effective moisture diffusion coefficient, m 2 /d；
t-drying time, d; l is the general height, m, of the grain layer thickness of the grains;
as can be seen from the formula (6), the effective water diffusion coefficient D of the grain layer can be calculated by drawing a curve between the lnMR and the time t and linearly fitting the curve according to the obtained slope eff ；
5. Mathematical model fitness evaluation equation
Carrying out data fitting on grain in-situ drying by 8 common mathematical models, and judging the model which is most suitable for the change of the moisture content of each layer of the grain pile in the in-situ drying ventilation process in the 8 mathematical models according to the correlation coefficient R2 and root mean square error (root mean square error, RMSE) of fitting results; the calculation formula is as follows:
wherein MR is Actual measurement value -a certain data point test measured moisture ratio; MR (magnetic resonance) Analog value -predicting the resulting moisture ratio from the mathematical model for a certain data point; n—number of test data points; the fitting degree between the mathematical model and the measured value can be based on the correlation coefficient R 2 And root mean square error RMSE, wherein the correlation coefficient R 2 The closer to 1The smaller the root mean square error RMSE value, the better the fitting of the equation.
Table 2 eight dry mathematical models
Note that: in the table, y represents the water percentage; x represents time (d), and the same applies below.
1.3 data processing
All indicators were assayed in 3 replicates, plotted using Origin 9.1 software, and data analyzed using SPSS25.0 for one-way ANOVA.
2. Results and analysis
2.1 Water migration law of grain pile
As shown in FIG. 4, the moisture content of each layer of the grain pile shows a decreasing trend, and as shown in A of FIG. 4, the moisture content of each layer of the grain pile shows a decreasing trend at 104m 3 Under the ventilation condition/h, the moisture content of the grains at the position 75-90 cm away from the grain surface is reduced to 12.13% and 11.74% respectively at 8d faster than the moisture content of the grains at other grain layers due to the direct contact with the air distribution chamber, and the moisture content difference measured by each sampling is obvious (P)<0.05 A) is provided; the water of the middle two layers (45-60 cm) drops at a second time, and the water of the two layers (15-30 cm) on the surface of the grain pile drops at a relatively slowest speed. Therefore, under the maximum ventilation condition set in the test, the grain pile moisture migrates upwards from the bottom, and the moisture of two layers of grains (75-90 cm) at the bottom can be reduced below the safe storage moisture at 8d, so that the requirements of GB/T26880-2011 (grain and oil storage and warehouse drying technical specification) are met. The bottom most moisture content of the stack of fig. 4B drops most rapidly, but the remaining layers all have a slight upward trend in moisture content at 2 d; as shown in fig. 4C, under the lowest aeration conditions, the water content of the grain pile drops most slowly than the other two sets of aeration conditions, and at 8d the water content drops to 13.07% at the bottom, probably because the bottom is in direct contact with the air distribution chamber, the water content in the grains can be rapidly discharged, the water content migrates from the bottom to the upper part of the grain pile, and the higher the aeration quantity, the faster the water drop speed, and the higher the upward migration speed of the water content of the grain pile. Meanwhile, as the grain pile is thicker and the environment humidity of the simulated bin is higher, the moisture in the grain pile is communicatedThe moisture content of the rest layers in the grain pile is slightly raised due to the fact that the moisture cannot migrate outwards in a short time under the condition of small air quantity, the water dropping speed is reduced, and the moisture in the grain pile can still migrate continuously from the bottom to the surface along with the increase of the drying time.
2.2 Effect of air quantity on drying Rate of grain pile
a-C of fig. 5 show the change in moisture drying rate of each layer of cereal under three ventilation levels, respectively. As can be seen from a of fig. 5, the grain moisture at the bottommost layer of the grain stack is in a state of rapid precipitation and then tends to balance precipitation, the first 6d is in a rapid precipitation stage, the moisture falling rate is relatively fastest, the ventilation drying rate is gradually gentle after 6d, and the average moisture content of the 6d grain layer is already lower than 14% in the balanced precipitation stage; at the position 75cm away from the surface of the grain pile, the grain drying rate is firstly increased and then decreased, and finally the grain drying rate tends to be in a constant-speed descending state; the precipitation rule of the grain layer at the position 60cm away from the surface of the grain pile mainly comprises two parts, namely a rapid precipitation stage and a slow precipitation stage; the precipitation rule of the upper half grain layer of the grain pile is always in the rapid precipitation stage.
As can be seen from fig. 5 (B), the bottommost cereal precipitation process includes: a rapid water-reducing stage, a slow water-reducing stage and a constant-speed water-reducing stage; the grain precipitation rate of each grain layer is in a trend of rising and then falling at the positions 75cm away from the surfaces of the grain piles, turning occurs at the precipitation rate of the 4 th d (moisture content < 18%), and turning occurs at the rest grain layers at the 6 th d (moisture content < 18%), wherein the grain precipitation rate of each grain layer is in a trend of rising and then falling; the grain precipitation is in the rapid water-reducing stage at the uppermost grain layer of the grain stack.
As can be seen from fig. 5 (C), the grain moisture decreasing rate at 90cm from the surface shows a tendency to increase first and then decrease last, and the average moisture content of the grain layer is not lower than 14% until 8 d; the grain drying rate is in a trend of rising and then falling at a position 75cm and 60cm away from the surface of the grain pile; and the drying rates of the other three layers are turned at the 4 th day, and the drying rates are increased after the 4 th day.
When the moisture content of the grain layer is more than 18%, the grain moisture drying rate is gradually accelerated to show a rapid water-reducing trend, and when the moisture content is between 14 and 18%, the drying rate is reduced to a moisture content lower than 14%The internal and external moisture of the grains are balanced, and the drying speed is close to a constant speed. Analyzing the reason, the grain at the bottom layer is in direct contact with the air distribution chamber, when the moisture content of the grain is too high>20 percent of moisture on the surface of the grains can be rapidly taken away, and the ventilation rate is 104m 3 At/h, the grain moisture can be rapidly reduced to 14%, so that the grain moisture does not undergo slow water reduction, but is 80m and 92m 3 In the ventilation condition/h, the wind speed is slower, and the slow water dropping stage of 14-18% period is needed.
2.3 Effect of ventilation on grain moisture percentage of each layer
The water ratio (MR) refers to the residual water ratio of the material under certain drying conditions, and can indirectly reflect the drying rate under the conditions. As can be seen from fig. 6, under three ventilation conditions, the grain moisture ratio showed a decreasing trend with the prolongation of the ventilation drying time, and the lowest layer was in direct contact with the air distribution chamber, the moisture ratio was the smallest, which indicated that the more moisture was lost from the grain pile, the greater the ventilation amount, and the faster the moisture ratio decreased. Since the initial moisture content of the grains was lower than the other two ventilation rates (see Table 1), at 92m 3 In the aeration condition/h, the grain water ratio of the first 4d is larger than that of the other two aeration conditions, as shown in a B of fig. 6, and especially in the 2d, the grain water ratio is larger than 1 except the bottom layer; the water ratio of the water drops faster within 2-4 d, and the water ratio of 4-6 d is compared with 104m 3 The ratio of the water to the water is smaller and larger than 80m 3 The moisture percentage of each layer under the ventilation rate is/h, and the moisture of the grain layer is slowly reduced at the moment, which is consistent with the condition of reduced drying rate; under each ventilation condition, the water ratio value of the grain layer at the bottommost layer is always smaller, but the earlier-stage change is larger, so that the water in the grain layer at the bottommost layer in the earlier stage (2 d) is rapidly reduced, and the later-stage reduction speed is gradually gentle. The analysis causes that the ventilation quantity is larger, the air pressure formed on the surface layer of the grain seeds is higher, so that the moisture on the surface of the grains can be rapidly taken away; the decrease of the moisture ratio in the later drying stage may be due to the decrease of the moisture content in the grains in the later drying stage, the gradient of the moisture in the grains gradually decreases, the moisture gradually tends to be balanced, and the moisture is difficult to decrease due to mechanical ventilation, so the moisture ratio is lower and lower under all ventilation conditions.
2.4 Effect of ventilation on effective diffusion coefficient of grain layer
The effective diffusion coefficient of the grain layer can be obtained by linear fitting (figure 4) of lnMR and t according to the formula (5) and the formula (6) to obtain the slope k1 of the fit equation, and the effective diffusion coefficient of each layer of grain under different ventilation conditions can be calculated according to the formula (6). The slope of the resulting fit equation for each layer and the effective diffusion coefficient are shown in Table 4.
TABLE 4 influence of ventilation on the effective diffusion coefficient of moisture in each layer of a grain pile
| Ventilation quantity (m) 3 /h) | Position (cm) | Slope k 1 | Effective diffusion coefficient (10) -3 m 2 /d) |
| 104 | 15cm | -0.083 | 0.19 |
| 30cm | -0.085 | 0.19 | |
| 45cm | -0.13 | 0.29 | |
| 60cm | -0.18 | 0.41 | |
| 75cm | -0.16 | 0.37 | |
| 90cm | -0.14 | 0.34 | |
| 92 | 15cm | -0.080 | 0.18 |
| 30cm | -0.12 | 0.27 | |
| 45cm | -0.12 | 0.28 | |
| 60cm | -0.17 | 0.38 | |
| 75cm | -0.19 | 0.43 | |
| 90cm | -0.17 | 0.39 | |
| 80 | 15cm | -0.0401 | 0.092 |
| 30cm | -0.0738 | 0.17 | |
| 45cm | -0.0849 | 0.19 | |
| 60cm | -0.12093 | 0.28 | |
| 75cm | -0.1526 | 0.35 | |
| 90cm | -0.13834 | 0.32 |
The effective water diffusion coefficient is an important index for representing the water diffusion condition in the material and reflects the dewatering capability of the material under a certain drying condition. As can be seen from Table 4, the effective water diffusion coefficient of the grain layer under three ventilation conditions is 0.092 to 0.43X10 -3 m 2 Varying within/d, 80m 3 Under the ventilation condition/h, the effective diffusion coefficient of the moisture of each layer of the grain stack is smaller than that of other two ventilation conditions, which is probably due to the fact that the wind speed is smaller, the pushing force born by the moisture in the grain when the moisture is diffused to the surface along the capillary tube is reduced, the difficulty of moisture diffusion is increased, and the effective diffusion coefficient is reduced; under the same ventilation condition, the effective diffusion coefficient of each layer of moisture of the grains is found that the diffusion coefficient of each layer of moisture of the grains is relatively larger within the range of 60-90 cm from the grain surface, and the grain moisture migration rule obtained by combining the results is as follows: the moisture migrates from the lower part of the grain pile to the upper part of the grain pile, the moisture content of the grain pile is generally higher within the range of 15-45 cm, and the moisture at the bottom is adhered to the surface of the grains at the upper part after migrating upwards, so that the activity of the moisture of the grains is weaker within the range, and the moisture diffusion coefficient of the grains is relatively smaller.
2.5 selection of the mathematical model for Bin drying
The drying modes are different, and the corresponding drying mathematical models are also different, so that the mathematical model which is most suitable for bin drying is accurately and effectively screened out, and the drying mathematical model is 104m 3 Under/h ventilation conditions, a common 8 dry mathematical models were used to fit curves to the grain water ratio change at 15cm, 75 cm. R is obtained according to fitting equation 2 And RMSE to measure the fit degree of the model to the dry ventilation regulation and control means of the in-place warehouse, and screening the optimal mathematical model to predict the ventilation condition of the dry to each grain pileInfluence of moisture content of the cereal grains. The fitting graph is shown in fig. 7, and the fitting result is shown in table 5:
TABLE 5 104m 3 15cm and 75cm equation simulation result under/h ventilation condition and related parameter determination
| Position (cm) | Model name | Equation parameters | R 2 |
| 15 | Page | k＝0.0075；n＝2.59 | 0.937 |
| Modified Page | k＝0.10；n＝2.59 | 0.937 | |
| Henderson&Pabis | a＝1.14；k＝0.073 | 0.747 | |
| Wang&Singh | a＝0.00073；b＝0.0067 | 0.947 | |
| Wang et al. | a＝0.93；k＝0.00013；n＝3.99 | 0.999 | |
| Binomial | a＝0.85；b＝0.066；c＝-0.013 | 0.995 | |
| Logarithmic | a＝-529.52；b＝530.62,k＝0.00016 | 0.632 | |
| Diffusion approach | a＝36.72；b＝1.03；k＝0.18 | 0.725 | |
| 75 | Page | k＝0.084；n＝1.28 | 0.987 |
| Modified Page | k＝0.15；n＝1.28 | 0.987 | |
| Henderson&Pabis | a＝1.16；k＝0.17 | 0.998 | |
| Wang&Singh | a＝-0.11；b＝0.0027 | 0.971 | |
| Wang et al. | a＝1.36；k＝0.28；n＝0.80 | 0.999 | |
| Binomial | a＝1.15；b＝-0.17；c＝0.0087 | 0.997 | |
| Logarithmic | a＝0.11；b＝1.11；k＝0.21 | 0.999 | |
| Diffusion approach | a＝1.16；b＝165.99；k＝0.17 | 0.996 |
As can be seen from Table 5, R is obtained by comparing 8 mathematical models 2 And RMSE values, where Wang et al model R 2 Reaching 0.999 and 75cm of the prescription process corresponds to RMSE values as low as 0.0054, much less than the rest of the model. Comprehensively considering, wang et al, the model is the most accurate and can be used for predicting the water diffusion change condition of each grain layer of grains under different ventilation conditions in the test. The water ratio versus time relationship and fit of the Wang et al model to the remaining layers was applied and the results are shown in Table 6: fitting curve correlation coefficient R 2 The RMSE values are all larger than 0.90 and smaller than 0.19, which indicates that the Wang et al model is used for predicting the influence of different wind speed conditions of the bin drying on the moisture change of each layer of the grain pile.
TABLE 6 simulation parameters of each layer of mathematical model
2.6 mathematical model verification
Under the condition of randomly selecting three ventilation volumes, the positions are respectively 90cm, 60cm and 30cm, and the 8d moisture change condition of the grains can be respectively represented by the following equation:
R 2 ＝0.996；/>
R 2 ＝0.961；
R 2 the water percentage during the grain layer drying period under this condition was calculated by means of a =0.969 prediction, the results of which are shown in table 7.
TABLE 7 comparison of moisture ratio measured values with simulated values
| Ventilation quantity (m) 3 /h) | Position (cm) | Actual measurement value | Analog value | Relative error (%) |
| 104 | 90 | 0.290 | 0.297 | 2.414 |
| 92 | 60 | 0.390 | 0.376 | 3.590 |
| 80 | 30 | 0.610 | 0.622 | 1.967 |
As can be seen from Table 7, the relative error between the actual grain water ratio measurement value and the equation prediction value is less than 5%, and 15% accuracy is required by the simulation of the average numerical value, so that the prediction model is reliable for predicting the change of the water content of each layer of the grain pile under different ventilation conditions of the drying of the just-in-warehouse.
(1) Under three ventilation conditions, the grain pile moisture migration rule is: the moisture migrates from the bottom of the grain pile to the upper part of the grain pile, and the higher the ventilation quantity is in a certain range, the faster the moisture dropping speed is, and the faster the upward migration speed of the moisture of the grain pile is. The larger the ventilation quantity is under the same environmental condition, the faster the moisture dropping speed of the grain pile is, and the more uniform the moisture distribution of each grain layer is;
(2) The bottom layer of the grain pile has a drying rate within 8 days, which basically comprises: a stage of rapid precipitation, slow precipitation and constant-speed precipitation; when the moisture content of the grain layer is more than 18%, the grain moisture drying rate is gradually increased, and when the moisture content is between 14 and 18%, the drying rate is reduced, and when the moisture content is lower than 14%, the moisture inside and outside the grain is balanced, and the drying rate is close to a constant speed; the grain precipitation rate of each grain layer is in a trend of rising and then falling at the positions 75, 60 and 45cm away from the surface of the grain pile; the grain precipitation is in a rapid water-reducing stage at the uppermost grain layer of the grain stack;
(3) The water ratio was calculated to find that: the grain layer moisture ratio shows a decreasing trend along with the extension of the ventilation drying time, and the moisture ratio of the bottommost layer in direct contact with the air distribution chamber is minimum; the effective water diffusion coefficient is 0.092-0.43X10 -3 m 2 Vary within/d range, and 80m 3 Under the ventilation condition/h, the effective diffusion coefficient of the moisture of each layer of the grain stack is smaller than that of other two ventilation conditions;
(4) R by comparison of eight mathematical models 2 And the RMSE value is finally determined, a mathematical model for drying each layer of the grain pile under different ventilation conditions can be established based on the Wang et al model, the moisture change condition of the grain pile under different ventilation conditions is predicted, the 8d moisture ratio of the bottommost layer of the grain pile under three ventilation conditions is selected randomly, the relative error between the predicted value and the measured value obtained by comparing the predicted model is less than 10%, the accuracy requirement of 15% of the general numerical simulation is lower, and the predicted model is reliable.
The foregoing description of the preferred embodiment of the invention is not intended to be limiting in any way, but rather, it is intended to cover all modifications or variations of the invention which fall within the spirit and scope of the invention.
Claims (1)
1. A method for measuring the migration rule of dry moisture in a grain bin is characterized by comprising the following steps: comprises a simulation bin, the simulation bin comprises a cylindrical bin body, and the top of the bin body is connected with a conical bin top in a sealing way; the bottom of the inner side of the simulation bin is provided with a bottom plate for placing grains, the bottom plate is uniformly provided with a plurality of through holes, the bottom plate and the bottom of the bin body form an air distribution chamber, one side of the air distribution chamber is provided with an air inlet, the other side of the air distribution chamber is provided with an air outlet, and the air inlet is communicated with an air supply device through a pipeline; the middle part of the bin body is provided with a temperature and humidity detection cable, and each temperature and humidity detection cable is provided with a temperature and humidity sensor at a certain distance; a plurality of sampling points are uniformly arranged at the plane positions corresponding to the temperature and humidity sensors;
the measuring method comprises the following steps:
(1) Determining total ventilation
The total ventilation quantity refers to the total air volume passing through the ventilation system in unit time, and the calculation formula is as follows:
Q total (S) =q×v×r, formula (1);
Q total (S) Total ventilation, m 3 /h; q-unit ventilation, m 3 /(h·t)；
V-volume of grain pile, m 3 The method comprises the steps of carrying out a first treatment on the surface of the r-grain volume weight, t/m 3 ；
(2) Initial conditions:
placing the experimental bin at the ambient temperature to be T 0 DEG C, relative humidity of RH 0 % room, pouring grains into a simulation bin to a position of 1m scale marks in the bin, sampling every 1d at sampling points for each batch of grains with total weight of 300kg, and measuring the moisture content of the grains at the sampling points until at least one layer of safe storage moisture with the moisture content as low as 14% exists in the grain pile;
(3) The measuring method comprises the following steps:
I. the method for calculating the drying rate of the grain is as follows:
wherein: v i -drying rate of cereal at moment i/(%/d); omega i -moisture mass fraction of cereal at moment i/%; omega t -grain moisture mass fraction/%;
II. Calculation of the Water percentage
The method for calculating the moisture ratio of the grains at the time t of bin drying is as follows:
wherein, the grain water ratio at the moment of MR-t; m is M t -drying the moisture content,%;
M 0 -initial moisture content of cereal,%; m is M e -grain equilibrium moisture content,%;
III, grain Balancing moisture M e The calculation method is as follows:
wherein RH—relative humidity,%; t (T) a -absolute temperature of the grain stack, K;
IV, the effective moisture diffusion coefficient calculation method is as follows:
taking the logarithm of equation (5) on both sides, and letting n=1, equation (6) can be obtained:
wherein, the grain water ratio at the moment of MR-t; d (D) eff Effective moisture diffusion coefficient, m 2 /d；
t-drying time, d; l is the general height, m, of the grain layer thickness of the grains;
as can be seen from the formula (6), the effective water diffusion coefficient D of the grain layer can be calculated by drawing a curve between the lnMR and the time t and linearly fitting the curve eff ；
V, mathematical model fitness evaluation equation
Data fitting is carried out on grain in-situ drying through 8 drying mathematical models, and the correlation coefficient R of fitting results is used 2 And judging the most suitable model for the change of the moisture content of each layer of grain pile in the drying and ventilation process of the warehouse in 8 mathematical models by the root mean square error; the calculation formula is as follows:
the 8 dry mathematical models are as follows:
1. the model name is Page, and the model equation is that
2. The model is named as Modified Page, and the model equation is named as
3. Model name Henderson&Pabis, model equation y=ae -kx ；
4. Model name Wang&Singh, model equation y=1+ax+bx 2 ；
5. The model name was Wang et al, and the model equation was
6. The model name is Binomial, and the model equation is y=a+bx+cx 2 ；
7. The model name is Logarithmic, and the model equation is y=a+be -kx ；
8. Model name Diffusion approach, model equation y=ae -kx +(1-a)e -kbx ；
Wherein MR is Actual measurement value -a certain data point test measured moisture ratio; MR (magnetic resonance) Analog value -predicting the resulting water percentage by a certain data point according to a mathematical model; n—number of test data points; the fitting degree between 8 dry mathematical models and the measured value can be based on the correlation coefficient R 2 And Root Mean Square Error (RMSE) when the correlation coefficient R 2 The closer to 1, the smaller the root mean square error RMSE value, which illustrates the better fit of the equation.
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