Prediction method and system for moisture at outlet of cut tobacco dryer

Abstract

The invention discloses a cut tobacco dryer outlet moisture prediction method and system, and belongs to the technical field of cut tobacco outlet moisture prediction. The method comprises the following steps: acquiring a boundary condition outside a cylinder of the cut tobacco dryer; the outside-cylinder boundary condition comprises a historical outside-cylinder boundary condition and a current outside-cylinder boundary condition; inputting the historical cylinder outer boundary conditions into a pre-constructed fuzzy rule classification model, and outputting a current working condition stage; inputting the current cylinder exterior boundary condition and a cylinder interior boundary condition fed back by the drying cylinder mechanism model into a pre-constructed heat and mass transfer regression algorithm model, and outputting a cylinder interior heat and mass transfer coefficient; and inputting the current boundary condition outside the cylinder, the current working condition and the heat and mass transfer coefficient in the cylinder into a pre-constructed drying cylinder mechanism model, and outputting a predicted value of the moisture at the outlet of the cut tobacco dryer. According to the method, various limiting conditions existing in actual production can be considered, the cut tobacco dryer mechanism model and the data model are organically combined, and the cut tobacco outlet moisture of the cut tobacco dryer under given conditions can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of predicting the moisture content of cut tobacco at the outlet, and in particular to a method and system for predicting the moisture content at the outlet of a cut tobacco dryer. Background Art

[0002] For predicting the moisture content at the outlet of a cut tobacco dryer, there are currently two main types of means:

[0003] One is mechanism modeling prediction. Such methods are based on the principles of thermodynamics, describe the heat and mass transfer processes in the cut tobacco dryer in the form of physical formulas, and summarize them into mathematical equations for solution by a computer.

[0004] There are mainly two implementation forms in mechanism modeling for predicting the outlet moisture content. One is to ignore the convective mass transfer process of the cut tobacco in the cut tobacco dryer and the energy change in the cut tobacco dryer, use Fick's second law to characterize the diffusion process, and use the Arrhenius formula to correct the diffusion coefficient; the other is to establish the convective heat and mass transfer formulas among the cut tobacco, moisture, and hot air in the cut tobacco dryer and calculate the energy change in the moisture migration process. These two implementation forms both ignore or simplify some factors in terms of mechanism and cannot take into account the complex state inside the cut tobacco dryer during actual operation. On the one hand, the theoretical calculated value can often only predict the ideal state under the given conditions in the laboratory, and it is difficult to guarantee the accuracy once the conditions are switched; on the other hand, the influence of disturbance factors such as air leakage and temperature fluctuations generated in actual production cannot be considered in the theoretical calculation, which results in limited application of the mechanism model in predicting the moisture content at the outlet of the cut tobacco dryer.

[0005] The other type is data modeling prediction. Such methods use machine learning methods to extract rules and experiences from a large amount of data collected on-site or in the laboratory, and predict the outlet moisture content based on the given production state. Commonly used methods include Bayesian networks, long short-term memory networks, etc. According to the production characteristics and data characteristics of the cut tobacco dryer, these methods often need to collect a large amount of actual production data and perform long-term model training to achieve a high fitting accuracy. Using this method mainly brings two problems. One is that the trained model contains a large number of hyperparameters with unclear meanings. These parameters can only reflect the mathematical characteristics of the model and have no association with the actual physical entities, resulting in a lack of inputs with clear physical meanings for the control means of the model; the other is that the trained model has the risk of overfitting. In the case of changing the production conditions of the cut tobacco dryer, the aging of the cut tobacco dryer, or the replacement of the cut tobacco dryer, the accuracy of the model often drops significantly, and it is necessary to re-collect data and train, which is very time-consuming and laborious. Summary of the Invention

[0006] The object of the present invention is to overcome the deficiencies in the prior art and provide a method and system for predicting the moisture content at the outlet of a cut tobacco dryer, which can take into account various limiting conditions existing in actual production and organically combine the mechanism model of the cut tobacco dryer with various data models, and can accurately predict the moisture content of the cut tobacco at the outlet of the cut tobacco dryer under given conditions.

[0007] To achieve the above object, the present invention is implemented by the following technical solutions:

[0008] On the one hand, the present invention provides a method for predicting the moisture content at the outlet of a cut tobacco dryer, including:

[0009] Obtain the outer boundary conditions of the dryer cylinder; the outer boundary conditions of the cylinder include historical outer boundary conditions and current outer boundary conditions;

[0010] Input the historical outer boundary conditions of the cylinder into a pre-constructed fuzzy rule classification model and output the current working condition stage;

[0011] Input the current outer boundary conditions of the cylinder and the inner boundary conditions of the cylinder feedback by the dryer cylinder mechanism model into a pre-constructed heat and mass transfer regression algorithm model and output the heat and mass transfer coefficient inside the cylinder;

[0012] Input the current outer boundary conditions of the cylinder, the current working condition and the heat and mass transfer coefficient inside the cylinder into a pre-constructed dryer cylinder mechanism model and output the predicted value of the moisture content at the outlet of the cut tobacco dryer.

[0013] Optionally, it further includes:

[0014] Input the historical outer boundary conditions of the cylinder into a moisture residual correction model and output the correction value of the moisture content at the outlet of the cut tobacco dryer;

[0015] Use the correction value of the moisture content at the outlet of the cut tobacco dryer to correct the predicted value of the moisture content at the outlet of the cut tobacco dryer.

[0016] Optionally, the outer boundary conditions of the cylinder include cut tobacco flow rate, hot air temperature, hot air flow rate and cylinder wall temperature;

[0017] The current working condition stage includes a shutdown stage, a dry head stage, a stable stage and a dry tail stage.

[0018] Optionally, the construction of the fuzzy rule classification model includes:

[0019] Mark the shutdown stage, the dry head stage, the stable stage and the dry tail stage as four linearly independent vectors, and the four-dimensional vectors are [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1] respectively;

[0020] Construct a two-dimensional vector for distinguishing the dry head stage and the dry tail stage, and the two-dimensional vector is [moisture content, cumulative running time];

[0021] Based on the four-dimensional vector and the two-dimensional vector, a constructed fuzzy rule classification model is obtained.

[0022] Optionally, the processing steps of the heat and mass transfer regression algorithm model include:

[0023] According to the moisture ratio of cut tobacco during drying, calculate the logarithmic curve of the moisture ratio of cut tobacco during drying. The calculation formula for the logarithmic curve of the moisture ratio of cut tobacco during drying is:

[0024] ;

[0025] ;

[0026] Wherein, Moisture ratio of cut tobacco during drying; Represents the moisture content on dry basis of cut tobacco; Represents the equilibrium moisture content on dry basis of the sample; Represents the initial moisture content of cut tobacco; Represents the heat and mass transfer coefficient inside the cylinder; Represents the drying thickness; Represents the drying time;

[0027] Adopt the SVR regression algorithm. According to the current outer boundary conditions of the cylinder and the inner boundary conditions of the cylinder feedback by the dryer mechanism model, fit the logarithmic curve of the moisture ratio of cut tobacco during drying To obtain the slope of the curve; Calculate the heat and mass transfer coefficient inside the cylinder according to the slope of the curve .

[0028] Optionally, the processing steps of the dryer mechanism model include:

[0029] According to the preset interpolation table and the hot air temperature, calculate the relative humidity of the hot air, and use the Hendersen correlation formula and the preset physical property parameter table of cut tobacco to calculate the equilibrium humidity of the cut tobacco gas film water vapor;

[0030] According to the relative humidity of the hot air, calculate the equilibrium density of the hot air gas film water vapor, and according to the equilibrium humidity of the cut tobacco gas film water vapor, calculate the equilibrium density of the cut tobacco gas film water vapor;

[0031] According to the current working condition stage, the equilibrium density of the hot air gas film water vapor and the equilibrium density of the cut tobacco gas film water vapor, calculate the predicted value of the moisture content at the outlet of the cut tobacco dryer.

[0032] Optionally, the calculation formulas for the equilibrium density of the hot air gas film water vapor and the equilibrium density of the cut tobacco gas film water vapor are:

[0033] ;

[0034] ;

[0035] ;

[0036] Among them, and respectively represent the equilibrium density of water vapor in the gas film of hot air and cut tobacco; and respectively represent the temperature of hot air and the temperature of cut tobacco; represents the mass of hot air; and respectively represent the relative humidity of hot air and the equilibrium humidity of water vapor in the gas film of cut tobacco; and respectively represent the average temperature of hot air and the average temperature of cut tobacco; and represent the correlation coefficient; represents the equilibrium humidity of water vapor in the gas film on the surface of cut tobacco.

[0037] Optionally, the calculation formula for the predicted value of the moisture content at the outlet of the cut tobacco dryer is:

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] ;

[0044] ;

[0045] Among them, represents the moisture content rate of the moisture content at the outlet of the cut tobacco dryer in the dry head stage; represents the moisture content rate of the moisture content at the outlet of the cut tobacco dryer in the dry tail stage; represents the moisture content rate of the moisture content at the outlet of the cut tobacco dryer in the stable stage; represents the cut tobacco linear velocity; represents the cylinder rotation speed; represents the drum inclination angle; represents the residence time of the cut tobacco unit in the cylinder; represents the drum length; and respectively represent the moisture content rate of cut tobacco in the dry head stage and the moisture content rate of cut tobacco in the dry tail stage; represents the drying time; represents the drying end time; , represents the correlation coefficient; represents the convective mass transfer coefficient; represents the heat transfer area; , respectively represent the water vapor densities under the gas film equilibrium state of the hot air and cut tobacco.

[0046] In a second aspect, the present invention provides a prediction system for the moisture content at the outlet of a cut tobacco dryer, including a processor and a storage medium;

[0047] The storage medium is used to store instructions;

[0048] The processor is used to operate according to the instructions to execute the method according to the first aspect.

[0049] In a third aspect, the present invention provides a computer-readable storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of the method according to the first aspect are realized.

[0050] Compared with the prior art, the beneficial effects achieved by the present invention:

[0051] The present invention combines the advantages of mechanism modeling and data modeling. Through the dryer mechanism model, its physical meaning is clear and interpretable. For the influence of working conditions and the actual diffusion coefficient of cut tobacco that cannot be considered in the mechanism model, they are respectively fitted by the fuzzy rule classification model and the heat and mass transfer regression algorithm model; there is one-way and two-way data interaction between each sub-model, and the model can be automatically corrected under conditions such as the update of external production collected data or the aging of the cut tobacco dryer, and the adaptive update is realized through the moisture residual correction model, so as to achieve higher prediction accuracy and prediction stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The following shows a schematic flow chart of the prediction method for the moisture content at the outlet of the cut tobacco dryer of the present invention in an embodiment;

[0053] Figure 2 The following shows a schematic discrete modeling diagram of the dryer mechanism model of the present invention in an embodiment;

[0054] Figure 3 The following shows a schematic comparison diagram of the predicted values of the moisture content at the outlet of the cut tobacco dryer of the present invention and the prior art in an embodiment;

[0055] Figure 4 The following shows a schematic comparison diagram of the predicted values of the moisture content at the outlet of the cut tobacco dryer of the present invention and the prior art in another embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0057] The term "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " generally represents an "or" relationship between the associated objects before and after.

[0058] Embodiment 1

[0059] As Figure 1 shown, this embodiment introduces a method for predicting the moisture content at the outlet of a cut tobacco dryer. By combining the advantages of mechanism modeling and data modeling, and at the same time making up for the shortcomings existing in the separate use of the two, through the dryer mechanism model, its physical meaning is clear and interpretable. For the influence of working conditions, the actual diffusion coefficient of cut tobacco, and environmental disturbances of the dryer that cannot be considered in the mechanism model, they are respectively fitted by a fuzzy rule classification model, a heat and mass transfer regression algorithm model, and a moisture residual correction model.

[0060] The method specifically includes the following steps:

[0061] Step 1: Obtain the outer boundary conditions of the dryer cylinder. The outer boundary conditions of the cylinder include historical outer boundary conditions and current outer boundary conditions. The outer boundary conditions of the cylinder include cut tobacco flow rate, hot air temperature, hot air flow rate, and cylinder wall temperature;

[0062] For the data acquisition result processing module, the data acquisition result processing module receives the original data collected by the sensor and performs certain preprocessing operations such as data filtering and data cleaning to obtain the outer boundary conditions of the cylinder, and then inputs the outer boundary conditions required by other models into the corresponding modules.

[0063] Step 2: Input the historical outer boundary conditions of the cylinder into a pre-constructed fuzzy rule classification model, and output the current working condition stage. Specifically:

[0064] For the fuzzy rule classification model, it mainly obtains the corresponding working condition stage after LSTM prediction and fuzzy rule classification based on the historical outer boundary conditions of the cylinder obtained by the data acquisition result processing module, and outputs it to the mechanism model. The current working condition stage includes a shutdown stage, a dry head stage, a stable stage, and a dry tail stage.

[0065] First, obtain the time-series data of the moisture content of cut tobacco from the inlet to the outlet of the drying cylinder through sensors, fill in the missing values, use the interpolation method to interpolate the discontinuous sampling data caused by equipment failures, generate an equally spaced time series, then perform noise filtering and smoothing processing to retain the characteristics of the moisture content change trend. Finally, use the maximum-minimum value method to map the moisture content data to the interval [0, 1] for normalization processing.

[0066] The construction of the fuzzy rule classification model includes:

[0067] First, mark the classification of the dry head stage and the dry tail stage. Respectively mark the shutdown stage, the dry head stage, the stable stage, and the dry tail stage as four linearly independent four-dimensional vectors: [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1], to avoid numerical interference between categories and prevent training instability caused by numerical magnitudes. Then, construct a two-dimensional vector [moisture content, cumulative running time] containing timestamps to avoid confusing scenarios between the dry head stage and the dry tail stage; according to the four-dimensional vector and the two-dimensional vector, obtain the constructed fuzzy rule classification model.

[0068] Construct a deep learning network containing a bidirectional LSTM layer, which includes an input layer, an LSTM layer, a Dropout layer, and a fully connected layer connected in sequence;

[0069] Input layer: 2 neurons, corresponding to the moisture content and time features. LSTM layer: The number of neurons is determined to be 32 through grid search. Dropout layer: The inactivation rate is 0.2. Fully connected layer: 4 neurons;

[0070] During the training process, adopt a variable learning rate strategy. In the initial stage of network training, perform iterative updates with a relatively large learning rate to quickly approach the lowest point and avoid falling into local optima; when the model residuals cannot continue to decrease within consecutive iterative steps, reduce the learning rate to precisely reach the lowest point and improve the model accuracy. In addition, introduce an L2 regularization term in the loss function with a coefficient λ = 0.01 to avoid overfitting in network training;

[0071] Convert it into a simulation model. The simulation model takes the moisture content of cut tobacco and time as inputs and the classification label as the output. 0 represents the shutdown stage, 1 represents the dry head stage, 2 represents the stable stage, and 3 represents the dry tail stage, and adjusts the solution strategy according to the working condition stage. For the dry head stage and the dry tail stage, since the flow rate of cut tobacco in the drum is less than the rated working condition, the dehumidification process is enhanced, and this phenomenon is more obvious at the beginning of the dry head and the end of the dry tail. Therefore, use an exponential function relationship to fit the gain of the dehumidification process that changes with time in the dry head and dry tail processes, and use different moisture content time derivative calculation formulas at different stages to ensure that the heat and mass transfer characteristics of different working condition stages can be fitted.

[0072] Step 3: Input the current outer cylinder boundary conditions and the inner cylinder boundary conditions feedback by the dryer mechanism model into a pre-constructed heat and mass transfer regression algorithm model to output the heat and mass transfer coefficients inside the cylinder. Specifically:

[0073] For the heat and mass transfer regression algorithm model, it calculates based on the outer cylinder boundary conditions (hot air temperature, cylinder wall temperature) input by the data acquisition result processing module and the inner cylinder boundary conditions (tobacco temperature, tobacco moisture content) calculated by the dryer mechanism model, obtains the moisture diffusion coefficient of the tobacco at the corresponding position under the given dryer boundary conditions, and outputs it to the dryer mechanism model as the heat and mass transfer coefficient inside the cylinder;

[0074] There are two ways to express the wet content in tobacco: dry basis wet content and wet basis wet content, which are expressed as:

[0075] ;

[0076] ;

[0077] Among them, , represent the dry basis moisture content and the wet basis moisture content respectively; represents the mass of moisture in the wet tobacco; represents the mass of absolutely dry tobacco.

[0078] The meaning of the moisture ratio is the remaining moisture rate of the material under certain drying conditions, which reflects the drying speed of the tobacco leaves. Its calculation formula is as follows:

[0079] ;

[0080] Among them, tobacco drying moisture ratio; represents the dry basis moisture content of the tobacco; represents the dry basis equilibrium moisture content of the sample; represents the initial moisture content of the tobacco;

[0081] Since the equilibrium moisture content at the end of tobacco drying is relatively small compared to the general initial moisture content, it can be considered that is 0;

[0082] The drying medium transfers heat to the tobacco by convective heat transfer. After the tobacco is heated and its temperature rises, the moisture in the tobacco is transferred to the drying medium by vaporization to complete the mass transfer process. Assume the tobacco drying process as a thin layer drying. According to Fick's second law, establish a differential equation describing the drying process, and its analytical solution is:

[0083] ;

[0084] Omit its high-order terms, and then take the logarithm to obtain the logarithmic curve of the moisture ratio of the cut tobacco during drying. , expressed as:

[0085] ;

[0086] Among them, represents the heat and mass transfer coefficient inside the cylinder; represents the drying thickness; represents the drying time;

[0087] The above formula indicates that the natural logarithm of the moisture ratio during the cut tobacco drying period and the drying time t have a linear relationship. By using the data of different working conditions of the cut tobacco dryer (i.e., the outer boundary conditions and the inner boundary conditions of the cylinder), the SVR regression algorithm is used to fit the natural logarithm dry curve of the moisture ratio during the cut tobacco drying period, and its slope is obtained. According to the slope, the moisture diffusion coefficient, that is, the heat and mass transfer coefficient inside the cylinder is obtained. The heat and mass transfer regression algorithm model obtained in this way can calculate the heat and mass transfer coefficient of the cut tobacco at each place inside the cylinder when the parameters inside and outside the cut tobacco dryer cylinder are known .

[0088] Step 4: Input the current outer boundary conditions of the cylinder, the current working conditions, and the heat and mass transfer coefficient inside the cylinder into the pre-constructed dryer cylinder mechanism model, and output the predicted value of the moisture at the outlet of the cut tobacco dryer. Specifically:

[0089] For the dryer cylinder mechanism model, in the fusion model, the dryer cylinder mechanism model is the center of data interaction. It accepts the outer boundary condition data parsed by the data acquisition result processing module, the current working condition data calculated by the fuzzy rule classification model, and the heat and mass transfer coefficient inside the cylinder calculated by the heat and mass transfer regression algorithm model as inputs. After the internal calculation of the dryer cylinder mechanism model, the calculated value of the outlet moisture is obtained. Finally, the outlet moisture correction value calculated by the moisture residual correction model is superimposed to obtain the final outlet moisture output value. The specific calculation process is as follows:

[0090] As Figure 2 shown, the model is divided into two calculation regions, namely the cut tobacco region and the hot air region, and discrete modeling is adopted. There are convective heat transfer and convective mass transfer processes between the cut tobacco and the hot air. At the same time, the cylinder wall also has heat exchange with both the cut tobacco and the hot air. In addition, the latent heat absorbed by the moisture evaporation during the cut tobacco dehumidification process needs to be considered.

[0091] The cut tobacco dehumidification mechanism adopts the double-film theory, and the mass transfer flux can be written as the product of the convective mass transfer coefficient and the mass transfer driving force. The mass transfer driving force is expressed as the difference in water vapor density between the hot air on the cut tobacco surface and the gas film.

[0092] The calculation of the hot air region includes the following steps:

[0093] Mass conservation equation on the hot air side:

[0094] ;

[0095] The energy conservation equation on the hot air side is:

[0096] ;

[0097] ;

[0098] in, 、 Respectively represent the hot air flow entering and flowing out of the cylinder; Indicates the flow rate of water vapor evaporating from tobacco; Indicates the evaporation potential of water vapor absorbed by hot air; Indicates the amount of heat that the hot air is heated by the cylinder wall; Indicates the hot air inlet mass flow rate; represents the specific heat capacity of air; Indicates the temperature difference between the inlet and outlet of the hot air segment volume; represents the convective heat transfer correction coefficient; Indicates the convection heat transfer coefficient between the hot air and the cylinder wall; Indicates the convection heat exchange area between the hot air and the cylinder wall; Indicates the number of segments; represents the wall temperature of the i-th volume cylinder; 、 They represent the hot air inlet temperature and outlet temperature in the i-th volume respectively.

[0099] The calculation of tobacco area includes the following steps:

[0100] Mass conservation equation on the tobacco side:

[0101] ;

[0102] Energy conservation equation on the tobacco side:

[0103] ;

[0104] ;

[0105] ;

[0106] in, 、 Respectively represent the flow rate of tobacco entering and flowing out of the cylinder; Indicates the flow rate of tobacco in the cylinder; represents the specific heat capacity of steam; 、 respectively represent the steam temperature in the i-th volume section and the steam temperature in the (i + 1)-th volume section; represents the heat exchange amount between the steam and the cut tobacco; represents the heat exchange amount between the steam and the wall surface; represents the wall surface temperature;

[0107] The dehumidification process of the cut tobacco adopts the double-film theory. The time derivative of the cut tobacco moisture content is regarded as the mass transfer flux, which can be expressed as the product of the convective mass transfer coefficient and the mass transfer driving force. According to the double-film theory, the mass transfer driving force can be expressed as the difference between the equilibrium density of water vapor in the air film and the equilibrium density of water vapor in the air film on the cut tobacco surface.

[0108] The processing steps of the dryer mechanism model include:

[0109] Calculate the relative humidity of the hot air according to the preset interpolation table and the hot air temperature, and calculate the equilibrium humidity of water vapor in the air film of the cut tobacco by using the Hendersen correlation formula and the preset physical property parameter table of the cut tobacco;

[0110] The preset interpolation table is shown in Table 1 and is expressed as:

[0111] When the hot air temperature is 338.15K, the relative humidity of the hot air is 0.115%;

[0112] When the hot air temperature is 358.15K, the relative humidity of the hot air is 0.050%;

[0113] When the hot air temperature is 378.15K, the relative humidity of the hot air is 0.024%;

[0114] When the hot air temperature is 398.15K, the relative humidity of the hot air is 0.012%;

[0115] When the hot air temperature is 418.15K, the relative humidity of the hot air is 0.007%;

[0116] The preset physical property parameter table of the cut tobacco is shown in Table 2 and is expressed as:

[0117] When the cut tobacco temperature is 338.15K, the equilibrium humidity of the air film on the cut tobacco surface is 0.048%;

[0118] When the cut tobacco temperature is 358.15K, the equilibrium humidity of the air film on the cut tobacco surface is 0.035%;

[0119] When the cut tobacco temperature is 378.15K, the equilibrium humidity of the air film on the cut tobacco surface is 0.027%;

[0120] When the cut tobacco temperature is 398.15K, the equilibrium humidity of the air film on the cut tobacco surface is 0.022%;

[0121] When the temperature of the cut tobacco is 418.15K, the equilibrium humidity of the gas film on the surface of the cut tobacco is 0.018%.

[0122] Table 1 Preset interpolation table

[0123]

[0124] Table 2 Preset physical property parameter table of cut tobacco

[0125]

[0126] Calculate the equilibrium density of water vapor in the gas film of the hot air according to the relative humidity of the hot air, and calculate the equilibrium density of water vapor in the gas film of the cut tobacco according to the equilibrium humidity of water vapor in the gas film of the cut tobacco. The calculation formulas for the equilibrium density of water vapor in the gas film of the hot air and the equilibrium density of water vapor in the gas film of the cut tobacco are as follows:

[0127] ;

[0128] ;

[0129] ;

[0130] Wherein, 、 respectively represent the equilibrium density of water vapor in the gas film of the hot air and the cut tobacco; 、 respectively represent the temperature of the hot air and the temperature of the cut tobacco; represents the mass of the hot air; 、 respectively represent the relative humidity of the hot air and the equilibrium humidity of water vapor in the gas film of the cut tobacco; 、 respectively represent the average temperature of the hot air and the average temperature of the cut tobacco; 、 represent the correlation coefficient; represents the equilibrium humidity of the gas film on the surface of the cut tobacco;

[0131] Calculate the predicted value of the moisture content at the outlet of the cut tobacco dryer according to the current working condition stage, the equilibrium density of water vapor in the gas film of the hot air and the equilibrium density of water vapor in the gas film of the cut tobacco. The calculation formula for the predicted value of the moisture content at the outlet of the cut tobacco dryer is as follows:

[0132] ;

[0133] ;

[0134] ;

[0135] ;

[0136] ;

[0137] ;

[0138] ;

[0139] wherein, represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the dry head stage; represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the dry tail stage; represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the stable stage; represents the cut tobacco wire speed; represents the cylinder rotation speed; represents the drum inclination angle; represents the residence time of the cut tobacco unit in the cylinder; represents the drum length; 、 represent the moisture content rates of the cut tobacco in the dry head stage and the dry tail stage; represents the drying time; represents the drying end time; 、 represent the correlation coefficient; represents the convective mass transfer coefficient; represents the heat transfer area; 、 respectively represent the water vapor densities in the hot air and the cut tobacco under the gas film equilibrium state.

[0140] Step Five: Input the historical outer boundary conditions of the cylinder into the moisture residual correction model, and output the corrected value of the outlet moisture of the cut tobacco dryer, specifically:

[0141] For the moisture residual correction model, it mainly receives the historical outer boundary conditions of the cylinder obtained by the data acquisition result processing module, calculates the calculation deviation value of the outlet moisture by using time series prediction algorithms such as Transformer, outputs the corrected value of the outlet moisture of the cut tobacco dryer, and outputs the corrected value to the cut tobacco dryer mechanism model. Using the corrected value of the outlet moisture of the cut tobacco dryer, correct the predicted value of the outlet moisture of the cut tobacco dryer.

[0142] This embodiment fully considers various limiting conditions existing in actual production and organically combines the cut tobacco dryer mechanism model with various data models, designs a good model architecture to ensure reasonable data interaction and calculation process between modules. The cut tobacco dryer mechanism model provides inputs with clear physical meanings for the data model, and the data model analyzes the influence of disturbance factors such as the environment that cannot be accurately quantified by the mechanism model. The two complement each other.

[0143] Embodiment 2

[0144] Based on Embodiment 1, this embodiment introduces a specific experimental example of a method for predicting the moisture content at the outlet of a cut tobacco dryer, including:

[0145] Constructed using the production data of a certain cigarette factory as a training sample, and the method of Embodiment 1 is used to predict the moisture content at the outlet of the cut tobacco dryer. As Figure 3 shown is the comparison between the predicted value of the outlet moisture content calculated and the data of a certain original production batch.

[0146] From Figure 3 it can be seen that during the entire batch production stage (about 8.5 hours), the predicted value of the outlet moisture content of the cut tobacco dryer has a good fitting degree with the data acquisition result, and in the initial production stage, i.e., the dry head stage, and the end production stage, i.e., the dry tail stage, the current working condition stage can be accurately distinguished, and the prediction accuracy is 1.85%.

[0147] To reflect the accurate capture of the influence of various complex disturbance factors in the production conditions by the prediction method, Figure 4 the comparison result between the predicted value of the outlet moisture content of the cut tobacco dryer and the data acquisition result during the stable production stage (about 8.4 hours) in the entire production batch is shown. It can be seen that the prediction effect is good, and the prediction accuracy is 0.637%.

[0148] Embodiment 3

[0149] This embodiment introduces a prediction system for the moisture content at the outlet of a cut tobacco dryer, including a processor and a storage medium;

[0150] The storage medium is used to store instructions;

[0151] The processor is used to operate according to the instructions to execute the method according to Embodiment 1 or 2.

[0152] Embodiment 4

[0153] This embodiment introduces a computer-readable storage medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the steps of the method according to Embodiment 1 or 2 are implemented.

[0154] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0155] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0156] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction means, and the instruction means implements the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0158] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the claims of the present invention. All of these fall within the protection scope of the present invention.

Claims

1. A method for predicting the moisture content at the outlet of a cut tobacco dryer, characterized in that, Including: Obtain the outer boundary conditions of the drying cylinder of the cut tobacco dryer; the outer boundary conditions of the cylinder include historical outer boundary conditions and current outer boundary conditions; Input the historical outer boundary conditions of the cylinder into a pre-constructed fuzzy rule classification model, and output the current operating condition stage; Input the current outer boundary conditions of the cylinder and the inner boundary conditions of the drying cylinder feedback by the drying cylinder mechanism model into a pre-constructed heat and mass transfer regression algorithm model, and output the heat and mass transfer coefficient inside the cylinder; Input the current outer boundary conditions of the cylinder, the current operating condition, and the heat and mass transfer coefficient inside the cylinder into a pre-constructed drying cylinder mechanism model, and output the predicted value of the moisture content at the outlet of the cut tobacco dryer.

2. The prediction method for the moisture content at the outlet of the cut tobacco dryer according to claim 1, characterized in that, It also includes: Input the historical outer boundary conditions of the cylinder into a moisture residue correction model, and output the correction value of the moisture content at the outlet of the cut tobacco dryer; Use the correction value of the moisture content at the outlet of the cut tobacco dryer to correct the predicted value of the moisture content at the outlet of the cut tobacco dryer.

3. The prediction method for the moisture content at the outlet of the cut tobacco dryer according to claim 1, characterized in that, The outer boundary conditions of the cylinder include cut tobacco flow rate, hot air temperature, hot air flow rate, and cylinder wall temperature; The current operating condition stage includes a shutdown stage, a dry head stage, a stable stage, and a dry tail stage.

4. The method for predicting the moisture content at the outlet of the cut tobacco dryer according to claim 3, characterized in that The construction of the fuzzy rule classification model includes: Mark the shutdown stage, dry head stage, stable stage, and dry tail stage as four linearly independent vectors, and the four-dimensional vectors are [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1] respectively; Construct a two-dimensional vector for distinguishing the dry head stage and the dry tail stage, and the two-dimensional vector is [moisture content rate, cumulative operation time]; According to the four-dimensional vector and the two-dimensional vector, obtain the constructed fuzzy rule classification model.

5. The prediction method of the outlet moisture of the cut tobacco dryer according to claim 1, characterized in that, The processing steps of the heat and mass transfer regression algorithm model include: According to the cut tobacco drying moisture ratio, calculate the logarithmic curve of the cut tobacco drying moisture ratio, and the calculation formula of the logarithmic curve of the cut tobacco drying moisture ratio is: ； ； Among them, moisture ratio of cut tobacco during drying; represents the moisture content on dry basis of cut tobacco; represents the equilibrium moisture content on dry basis of the sample; represents the initial moisture content of cut tobacco; represents the heat and mass transfer coefficient in the cylinder; represents the drying thickness; represents the drying time; Using the SVR regression algorithm, according to the current outer boundary conditions of the cylinder and the inner boundary conditions of the cylinder feedback by the dryer cylinder mechanism model, the logarithmic curve of the moisture ratio of the cut tobacco during drying is fitted to obtain the slope of the curve; according to the slope of the curve, the heat and mass transfer coefficient inside the cylinder is calculated .

6. The prediction method of the moisture content at the outlet of the cut tobacco dryer according to claim 3, characterized in that, The processing steps of the drying cylinder mechanism model include: Calculate the relative humidity of the hot air according to the preset interpolation table and the hot air temperature, and calculate the equilibrium humidity of the water vapor in the gas film of the cut tobacco by using the Hendersen correlation formula and the preset cut tobacco physical property parameter table; Calculate the equilibrium density of the water vapor in the gas film of the hot air according to the relative humidity of the hot air, and calculate the equilibrium density of the water vapor in the gas film of the cut tobacco according to the equilibrium humidity of the water vapor in the gas film of the cut tobacco; According to the current operating condition stage, the equilibrium density of the water vapor in the gas film of the hot air, and the equilibrium density of the water vapor in the gas film of the cut tobacco, calculate the predicted value of the moisture content at the outlet of the cut tobacco dryer.

7. The prediction method of the outlet moisture of the cut tobacco dryer according to claim 6, characterized in that, The calculation formulas of the equilibrium density of the water vapor in the gas film of the hot air and the equilibrium density of the water vapor in the gas film of the cut tobacco are: ； ； ； Among them, and respectively represent the gas film water vapor equilibrium densities of hot air and cut tobacco; and respectively represent the hot air temperature and the cut tobacco temperature; represents the mass of hot air; and respectively represent the relative humidity of hot air and the gas film water vapor equilibrium humidity of cut tobacco; and respectively represent the average temperature of hot air and the average temperature of cut tobacco; and represent the correlation coefficients; represents the gas film equilibrium humidity on the surface of cut tobacco.

8. The prediction method of the moisture content at the outlet of the cut tobacco dryer according to claim 7, characterized in that, The calculation formula of the predicted value of the moisture content at the outlet of the cut tobacco dryer is: ； ； ； ； ； ； ； Among them, represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the dry head stage; represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the dry tail stage; represents the moisture content rate of the outlet moisture of the cut tobacco dryer in the stable stage; represents the cut tobacco wire speed; represents the cylinder rotation speed; represents the drum inclination angle; represents the residence time of the cut tobacco unit in the cylinder; represents the drum length; 、 represent the moisture content rate of the cut tobacco in the dry head stage and the moisture content rate of the cut tobacco in the dry tail stage; represents the drying time; represents the drying end time; 、 represent the correlation coefficient; represents the convective mass transfer coefficient; represents the heat transfer area; 、 respectively represent the water vapor density under the air film equilibrium state of the hot air and the cut tobacco.

9. A prediction system for the moisture content at the outlet of a cut tobacco dryer, characterized in that, Including a processor and a storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that, When the computer instructions are executed by the processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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