CN117647093B - Intelligent control method and equipment for water content in tea drying process - Google Patents
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Abstract
The invention discloses an intelligent control method and equipment for water content of tea leaf drying process, belonging to the technical field of intelligent control of tea leaf drying equipment; constructing a tea drying thin layer model, and fitting model parameters; calculating initial operation parameters of the dryer equipment through the tea drying thin layer model; and obtaining the difference value between the real-time water content of the tea and the target water content, and performing iterative calculation for a plurality of times to adjust the operation parameters of the drying equipment until the difference value between the real-time water content of the tea and the target water content meets the target value. According to the invention, the initial drying time is calculated by using the thin layer drying model during tea drying, then parameters in the thin layer drying model are continuously adjusted, the drying time is further adjusted, and the final moisture content of the dried tea is used as a technical index of production by combining a tea moisture real-time detector, so that the problem that the moisture content of the tea is difficult to accurately control in a drying link is solved, and the tea quality is improved.
Description
Technical Field
The invention relates to the technical field of intelligent control of tea drying equipment, and particularly discloses an intelligent control method and equipment for water content in a tea drying process.
Background
Drying is an essential link in the tea processing process, and mainly evaporates the moisture of the tea by heat, so that the unique sensory quality and stable quality characteristics of the tea are formed. In addition, the drying can promote chemical components in the tea to generate a series of complex chemical reactions, and further improve the aroma, taste and color of the tea. One of the important indexes of the proper drying degree is the moisture content of the dried leaves, and the moisture content after drying is too high, which means that the drying degree is insufficient, and the high moisture content can cause the tea leaves to lose the original aroma and taste, present the fermented and rancid taste and influence the quality and taste of the tea leaves; the moisture content after drying is too low, so that the tea leaves can be dried and fragile and easy to break, the aroma and the taste of the tea leaves can be lost, the taste becomes coarse, the taste and the quality of the tea leaves are affected, at present, in the tea baking processing process, the consistency of processing cannot be ensured mainly through manual control and adjustment, judgment is needed according to personal experience, the optimal state of the moisture content after drying of the tea leaves cannot be ensured, and the working efficiency is low.
The control precision can be improved by establishing a water content change model in the drying process, but the model parameters such as temperature, material thickness, drying time and the like are more, and according to the inventor's prior research and investigation related documents (Wang Zhenbin. Design research of an automatic control system of a forage grass solar-heat pump drying system material conveying device [ D ] inner Mongolian agricultural university, 2023 ]) the material thickness, the drying time and the water content change are often in a nonlinear relation. Therefore, the invention firstly builds a drying model oriented to the tea drying process, and on the basis, proposes an intelligent control scheme.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an intelligent control method and equipment for the water content in the tea drying process, so that the water content of the dried tea can reach an optimal value, the good quality and uniformity of the dried tea can be ensured, and the labor intensity of workers is reduced.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the intelligent control method for the water content of the tea leaf drying process is applied to tea leaf drying equipment, the drying equipment adopts a chain plate type dryer and a water content real-time detector arranged at a feed inlet and a discharge outlet of the dryer, and the method comprises the following steps:
acquiring operation parameters of drying equipment and the initial water content of tea;
constructing a tea drying thin layer model, and fitting model parameters;
calculating initial operation parameters of dryer equipment through the tea drying thin layer model;
obtaining a difference value between the real-time water content of the tea and the target water content, and performing iterative calculation for a plurality of times to adjust the operation parameters of the drying equipment until the difference value between the real-time water content of the tea and the target water content accords with the target value;
the tea drying thin layer model comprises:
；
wherein M is the final water content of tea, M 0 The initial water content of the tea is a drying temperature of the tea, b is a drying time, c is a thickness of the tea, alpha, beta and gamma are three parameters to be fitted of a tea thin layer drying model, a s Parameters are adjusted for temperature.
Further, the calculating the initial operation parameters of the dryer equipment through the tea drying thin layer model comprises the steps of roughly adjusting the operation parameters of the dryer equipment through updating model parameters in real time, and finely adjusting the operation parameters of the dryer equipment through a section two type fuzzy PI controller.
Further, also comprises
Acquiring a tea water content change data set under the conditions of different drying temperatures and tea thicknesses, and adopting least square problem estimation to solve parameters to be fitted:
；
recording the initial water content of tea in the data of the i group as M i0 The final water content is M i The drying temperature is a i Thickness c i Time b i The method comprises the steps of carrying out a first treatment on the surface of the Fitting by Gaussian Newton iteration method、/>、/>。
Further, the method comprises the specific steps of sequentially setting a first difference index, a second difference index and a third difference index from small to large to evaluate the difference value between the real-time water content of the tea and the target water content, and constructing an optimization model according to an evaluation result to optimize and adjust the operation parameters.
Further, constructing a model to calculate target operation parameters of the drying equipment:
；
；
wherein b is 0 D, for the drying time of the dryer 0 For the running speed of the dryer, M 1 Is the first water content of tea, M 2 Is the second component of teaWater ratio, M T For the target water content, a T C is the drying temperature of the dryer T For drying thickness, J is the number of layers of the chain plate, and L is the length of a single-layer chain plate.
Further, when the difference value is between the second difference value index and the third difference value index, a performance index function update is constructed、/>Pair b 0 And d 0 Coarse adjustment is carried out;
；
；
；
；
where t represents the current time and t-1 represents the last time.
Further, when the difference value is between the first difference index and the second difference index, the operation parameter optimization step is as follows:
constructing a difference function of the difference value between the real-time water content and the target water content;
construction interval two-type model approximation nonlinear functionOn-line regulation and control KpInput variable b 0 (t) and Δb 0 The fuzzy set of (t) is { P, N }, where "P" represents positive and "N" represents negative, let its argument be [0,1 ]]；
Nonlinear function of output variableIs { N, Z, P }, where N represents a nonlinear function +.>Negative, Z represents a nonlinear function +.>Zero, P represents a nonlinear functionIf yes, a fuzzy control rule base is formulated;
calculatingAnd constructing a function solution b 0 And d 0 Fine tuning is carried out;
；
；
；
wherein K is an adjustment coefficient, K P For the proportional adjustment factor, K I For the integral adjustment coefficient, η is the immune coefficient,is the difference between the current water content of tea leaves and the target water content, < >>Is the difference variable value of the water content of tea leaves and the target water content,>for the drying time at the present moment, < > and->Is the adjustment value of the drying time.
In a second aspect, the invention discloses a device comprising a memory and a processor, wherein the memory is used for storing a program for supporting the processor to execute the intelligent control method for the water content of the tea leaf drying process, and the processor is configured to execute the program stored in the memory.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the initial drying time is calculated by using the thin layer drying model during tea drying, then parameters in the thin layer drying model are continuously adjusted, the running speed of drying equipment is further adjusted so as to control the optimization of the drying time, and the final moisture content of the dried tea is used as an evaluation index for processing by combining a tea moisture real-time detector, so that the problem that the moisture content of the tea in a drying link is difficult to accurately control is solved, and the tea quality is improved.
Drawings
Fig. 1 is a schematic view of a tea leaf drying and processing device according to an embodiment of the present invention;
fig. 2 is a flow chart of intelligent control of tea leaf drying processing according to an embodiment of the invention;
FIG. 3 is a diagram showing a rough control of drying time according to an embodiment of the present invention;
FIG. 4 is a diagram showing a structure of a drying time fine adjustment control according to an embodiment of the present invention;
reference numerals in the drawings: 1-a first elevator; 2-a first tea moisture real-time detector; 3-chain plate dryer; 4-a second tea moisture real-time detector; 5-a second elevator.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, are within the scope of the present embodiments, based on the embodiments of the present disclosure.
In this embodiment, the tea drying device adopts the common chain plate dryer 3, uniformly bakes through setting multiple layers of chain plates, when drying, as shown in fig. 1, the tea is conveyed to the top chain plate of the chain plate dryer 3 through the first elevator 1, and is sequentially conveyed to the second elevator 5 through the multiple layers of chain plates, the first tea moisture real-time detector 2 and the second tea moisture real-time detector 4 are respectively arranged at the outlet of the first elevator 1 and the inlet of the second elevator 5 to monitor the moisture content of the tea at different stages in real time, the collected data is fed back to the control module, the collected data is evaluated through the algorithm model in the control module, the operation parameters of the dryer are further adjusted through the tea drying thin layer model, namely, the rotation speed of the dryer drum in the processing process is adjusted, the drying time of the tea is adjusted, and the moisture content of the tea is further controlled, so that the moisture content of the tea reaches the optimal value, and the aroma, the taste and the tea taste are further improved.
As shown in fig. 2, in this embodiment, the method for intelligently controlling the moisture content of the tea drying process includes the following steps:
acquiring operation parameters of drying equipment and the initial water content of tea;
constructing a tea drying thin layer model, and fitting model parameters;
calculating initial operation parameters of dryer equipment through the tea drying thin layer model;
obtaining a difference value between the real-time water content of the tea and the target water content, and performing iterative calculation for a plurality of times to adjust the operation parameters of the drying equipment until the difference value between the real-time water content of the tea and the target water content accords with the target value;
and calculating initial operation parameters of the dryer equipment through the tea drying thin layer model, wherein the steps of roughly adjusting the operation parameters of the dryer equipment through updating model parameters in real time and finely adjusting the operation parameters of the dryer equipment through a section two type fuzzy PI controller.
The specific operation steps are as follows:
step 1, constructing a tea drying thin layer model, and fitting model parameters;
step 1.1, constructing a thin layer drying model during tea fixation by using a formula (1.1):
； (1.1)
in the formula (1.1), M is the final water content of the tea, M 0 The initial water content of the tea is a drying temperature of the tea, b is a drying time, c is a thickness of the tea, alpha, beta and gamma are three parameters to be fitted of a tea thin layer drying model, a s For the temperature adjustment parameter, and have:
； (1.2)
in the formula (1.2), a j Measuring the temperature of each layer of the dryer, wherein J is the number of layers of the chain plate;
step 1.2, obtaining a tea water content change data set under the conditions of different drying temperatures and tea thickness, and recording the initial water content of tea in the ith group of data as M i0 The final water content is M i The drying temperature is a i Thickness c i Time b i ；
Step 1.3, estimating parameters to be fitted through solving the least square problem of (1.3);
； (1.3)
step 1.4, fitting by using a Gauss Newton iteration method to obtain、/>、/>。
Step 2, calculating the current drying time b of the chain-plate dryer 3 by using the formula (1.4) 0 The current speed of the operation of the chain plate in the chain plate dryer 3 is adjusted to d by the formula (1.5) 0 ；
； (1.4)
；(1.5)
Recording that the current water content is M by the first tea moisture detector 2 1 The second tea moisture detector 4 detects that the current moisture content is M 2 The method comprises the steps of carrying out a first treatment on the surface of the Setting the water content of the drying target as M T The drying temperature of the chain plate dryer 3 is a T The drying thickness is c T The method comprises the steps of carrying out a first treatment on the surface of the The single-layer chain plate of the chain plate dryer has the length L.
Step 3, judging: setting first, second and third difference indexes、/>、/>Evaluating the difference value between the real-time water content of the tea and the target water content, constructing an optimization model according to the evaluation result, and optimizing and adjusting the operation parameters, wherein +.>；
If it isReturning to the step 2;
if it isStep 4 is entered;
if it isStep 5 is entered;
if it isThe current running state of the dryer is maintained, and the water content of the tea leaves reaches the target value.
Step 4, coarse tuning the current drying time of the first chain plate dryer 3 to b 0 And adjusts the current speed of the operation of the chain plate in the first chain plate dryer 3 to d 0 Then enter step 3; the specific steps are as shown in fig. 3, the chain plate dryer 3 is regulated and controlled through a feedback mechanism, the real-time water content of tea after the drying process is detected through a tea moisture real-time detector, the real-time water content of tea is fed back to a control module to be compared with a target set value, if the real-time water content of tea is inconsistent with the target set value, parameters are updated, driving parameters of the chain plate dryer 3 are further regulated through a controller, and drying time is further optimized;
step 4.1, constructing a performance index function by using the formula (1.6);
； (1.6)
step 4.2, update with equations (1.7), (1.8)、/>；
； (1.7)
； (1.8)
； (1.9)
Delta alpha representsDelta beta represents->Delta gamma represents->Wherein t represents the current time and t-1 represents the last time;
step 4.3, calculating the current drying time of the chain plate dryer 3 as b by using the formula (1.4) 0 The speed of the operation of the chain plate in the chain plate dryer 3 is adjusted to d by the formula (1.5) 0 And then step 3 is carried out.
Step 5, finely adjusting the current drying time of the first chain plate dryer 3 to b 0 And adjusts the current speed of the operation of the chain plate in the first chain plate dryer 3 to d 0 Then enter step 3; in the drying process, the tea moisture is controlled by an immune feedback rule, and the interval two-stage fuzzy controller adjusts parameters of a set value PI controller according to real-time monitoring data of the tea moisture so as to realize the purpose of accurately controlling the tea moisture. In the figure, the set value is that the drying target water content is M T The output of the PI controller corresponds to the Chinese formula (1.23, 1.24) in the step 5.6 to calculate the drying time; the immune feedback rule corresponds to the formula (1.22) in step 5.6 to adjust K p Is a value of (2); interval two-type mold for use in output equation (1.22)The input is +.>And->，/>For the drying time at the present moment, < > and->Is the adjustment value of the drying time;
step 5.1, calculating the difference value between the current water content of the tea and the target water content by using a formula (1.10);
； (1.10)
step 5.2, constructing a second-class model approximation nonlinear functionOn-line regulation and control KpInput variable b 0 (t) and Δb 0 The fuzzy set of (t) is { P, N }, where "P" represents positive and "N" represents negative, let its argument be [0,1 ]]；
Construction of b Using formula (1.11) 0 (t) upper bound membership function when it is "N：
；(1.11)
Construction of b Using formula (1.12) 0 (t) Lower bound membership function in "N：
； (1.12)
Construction of b Using formula (1.13) 0 (t) Upper bound membership function at "P：
； (1.13)
By using (1.14)) Construction b 0 (t) Lower bound membership function at "P：
； (1.14)
Constructing Δb using formula (1.15) 0 (t) upper bound membership function when it is "N：
； (1.15)
Constructing Δb using formula (1.16) 0 (t) Lower bound membership function in "N：
； (1.16)
Constructing Δb using formula (1.17) 0 (t) Upper bound membership function at "P：
；(1.17)
Constructing Δb using formula (1.18) 0 (t) Lower bound membership function at "P：
； (1.18)
Step 5.3, transfusionOutput variable nonlinear functionIs { N, Z, P }, where N represents a nonlinear function +.>Negative, Z represents a nonlinear function +.>Zero, P represents a nonlinear functionIs positive;
let the upper limit value of N be f N H The lower limit of N isf N L The upper limit value of Z isf Z H The lower limit value of Z isf Z L The upper bound of P isf P H The lower limit of P isf P L ；
Step 5.4, formulating a fuzzy control rule base as shown in a table 1;
rule 1: if b 0 (t) Is "N", and Δb 0 Is "N", thenIs "P";
rule 2: if b 0 (t) Is "N", and Δb 0 Is "P", thenIs "Z";
rule 3: if b 0 (t) Is "P", and Δb 0 Is "N", thenIs "Z";
rule 4: if b 0 (t) Is "P", and Δb 0 Is "P", thenIs "N";
；
step 5.5 determination using the formulae (1.19), (1.20), (1.21)；
； (1.19)
； (1.20)
； (1.21)
Step 5.6, calculating the current drying time of the first link plate dryer 3 as b by using the formulas (1.22), (1.23) and (1.24) 0 And adjusts the current speed of the operation of the link plate in the first link plate dryer 3 to d by using the formula (1.5) 0 Then enter step 3;
； (1.22)
； (1.23)
； (1.24)
wherein K is an adjustment coefficient, K P For the proportional adjustment factor, K I For the integral adjustment coefficient, η is the immune coefficient,is the current tea leaf containingDifference between water ratio and target water ratio, +.>Is the difference variable value of the water content of the tea leaves and the target water content,for the drying time at the present moment, < > and->Is the adjustment value of the drying time.
In another embodiment, an electronic device includes a memory for storing a program for supporting the processor to execute the above-described intelligent control method, and a processor configured to execute the program stored in the memory.
In another embodiment, the invention discloses a computer readable storage medium, and a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to execute the steps of the intelligent control method for the water content of the tea drying process.
In the description of the present embodiment, it should be understood that the terms "upper", "lower", "left", "right", etc. indicate an orientation or a positional relationship based on that shown in the drawings, only for convenience of describing the present embodiment and simplifying the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be constructed or operated in a specific orientation, and thus should not be construed as limiting the present embodiment.
Furthermore, it is possible to provide a device for the treatment of a disease. The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. In the description of the present embodiment, the meaning of "several" means two or more, unless specifically defined otherwise.
It will be appreciated by those skilled in the art that numerous variations, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the embodiments. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the embodiments being indicated by the appended claims rather than by the foregoing description, and all changes, substitutions and alterations herein are intended to be included within the spirit and principles of the present embodiments.
Claims (6)
1. The intelligent control method for the water content of the tea leaf drying process is applied to tea leaf drying equipment, the drying equipment adopts a chain plate type dryer and a water content real-time detector arranged at a feed inlet and a discharge outlet of the dryer, and is characterized by comprising the following steps:
acquiring operation parameters of drying equipment and the initial water content of tea;
constructing a tea drying thin layer model, and fitting model parameters;
calculating initial operation parameters of dryer equipment through the tea drying thin layer model;
obtaining a difference value between the real-time water content of the tea and the target water content, and performing iterative calculation for a plurality of times to adjust the operation parameters of the drying equipment until the difference value between the real-time water content of the tea and the target water content accords with the target value; the method comprises the specific steps that a first difference index, a second difference index and a third difference index are sequentially arranged from small to large, the difference between the real-time water content of the tea and the target water content is evaluated, an optimization model is constructed according to the evaluation result, and the operation parameters are optimized and adjusted;
the tea drying thin layer model comprises:
；
wherein M is the final water content of tea, M 0 The initial water content of the tea is a drying temperature of the tea, b is a drying time, c is a thickness of the tea, alpha, beta and gamma are three parameters to be fitted of a tea thin layer drying model, a s Parameters are adjusted for temperature.
2. The intelligent control method for water content in a tea drying process according to claim 1, wherein the calculating the initial operation parameters of the dryer equipment by the tea drying thin layer model includes coarse tuning the operation parameters of the dryer equipment by updating model parameters in real time, and fine tuning the operation parameters of the dryer equipment by using a section type two fuzzy PI controller.
3. The intelligent control method for the water content of the tea leaf drying process according to claim 2, further comprising
Acquiring a tea water content change data set under the conditions of different drying temperatures and tea thicknesses, and adopting least square problem estimation to solve parameters to be fitted:
；
wherein, the initial water content of the tea in the data of the i group is recorded as M 0i The final water content is M i The drying temperature is a i Thickness c i Time b i The method comprises the steps of carrying out a first treatment on the surface of the Fitting by Gaussian Newton iteration method、/>、/>。
4. The intelligent control method for water content in a tea leaf drying process according to claim 3, wherein a model is constructed to calculate target operation parameters of the drying apparatus:
；
；
wherein b is 0 D, for the drying time of the dryer 0 For the running speed of the dryer, M 1 Is the first water content of tea, M 2 Is the second water content of the tea, M T For the target water content, a T C is the drying temperature of the dryer T For drying thickness, J is the number of layers of the chain plate, and L is the length of a single-layer chain plate.
5. The intelligent control method for water content in tea leaf drying process according to claim 4, wherein when the difference value is between the second difference value index and the third difference value index, the function update of the performance index is constructed、/>Pair b 0 And d 0 Coarse adjustment is carried out;
；
；
；
；
in the formula, t represents the current time, and t-1 represents the last time.
6. The intelligent control method for water content in tea leaf drying process according to claim 5, wherein when the difference value is between the first difference value index and the second difference value index, the operation parameter optimizing step is as follows:
constructing a difference function of the difference value between the real-time water content and the target water content;
construction interval two-type model approximation nonlinear functionOn-line regulation and control K p Input variable b 0 (t) and Δb 0 The fuzzy set of (t) is { P, N }, where "P" represents positive and "N" represents negative, let its argument be [0,1 ]]；
Nonlinear function of output variableIs { N, Z, P }, where N represents a nonlinear functionNegative, Z represents a nonlinear function +.>Zero, P represents a nonlinear functionIf yes, a fuzzy control rule base is formulated;
calculatingAnd constructing a function solution b 0 And d 0 Fine tuning is carried out;
；
；
；
wherein K is an adjustment coefficient, K P For the proportional adjustment factor, K I For the integral adjustment coefficient, η is the immune coefficient,is the difference between the current water content of tea leaves and the target water content, < >>Is the difference variable value of the water content of tea leaves and the target water content,>for the drying time at the present moment, < > and->Is the adjustment value of the drying time.
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