Customized and intelligent regulation and control method for tobacco leaf curing process

Abstract

A tobacco leaf curing process customization and intelligent regulation and control method comprises the following steps: (1) through curing barn temperature and humidity data acquisition and analysis, forming a'one-point three-frame one-rate 'curing process portrait; (2) on the basis of a tobacco leaf production area baking process portrait, personalized customization is carried out on process adjustment parameters (temperature stabilization time amplitude variation and wet bulb temperature amplitude variation) of a key temperature stabilization point, and a customized baking process model is established; (3) monitoring the tobacco leaf state and the environment temperature and humidity in a mode of installing a camera and a temperature and humidity sensor in the curing barn; and (4) comparing the tobacco leaf state monitored in the curing process with the customized curing process model requirement in real time, automatically forming a process adjustment instruction according to the matching degree of the tobacco leaf state and the target state, and spontaneously executing the process adjustment instruction through the curing barn control instrument. According to the method provided by the invention, the problems of low pertinence and high implementation difficulty of a customized production technical scheme can be effectively solved, and customized and intelligent regulation and control of tobacco leaf baking are realized.

Description

Technical Field

[0001] The invention relates to a customized and intelligent control method for a tobacco leaf baking process, and belongs to the field of tobacco leaf baking. Background Art

[0002] Customized tobacco leaf production refers to the process of developing tobacco leaf production technology plans, managing the production process, and delivering tobacco leaf products, tailored to the specific characteristics of tobacco-producing regions and the individual needs of tobacco industry enterprises. Tobacco leaf curing is a key step influencing tobacco leaf quality, determining its transformation from an agricultural product lacking commercial value to a raw material for the tobacco industry. Curing technology is a major factor influencing tobacco leaf curing quality. In recent years, domestic and international scholars have proposed curing methods such as the three-stage method, the five-stage five-corresponding method, and the eight-point method. These methods divide the tobacco leaf curing process into several stages or steady-state temperature points, and specify target wet-bulb temperatures and leaf yellowing and drying conditions for each steady-state temperature point. Overall, current curing methods are mostly generic, based on traditional experience or basic drying principles. However, due to differences in the ecological environment and tobacco varieties across different tobacco-producing regions, as well as the varying quality requirements of different tobacco industry enterprises, these curing methods lack specificity and are therefore limited in their practical application. There are limited reports on customized tobacco leaf baking. There is a lack of research on dynamic baking parameter models tailored to the needs of different cigarette brands, insufficient deep integration of intelligent control technology and production scenarios, and the real-time monitoring and feedback mechanism of multi-dimensional data of the baking process (such as temperature and humidity, and physical and chemical indicators of tobacco leaves) has not yet been systematized. Summary of the Invention

[0003] The purpose of this invention is to address the problems of the current customized tobacco production technology solutions being not very targeted and difficult to implement, and to provide a method for customizing and intelligently controlling tobacco baking processes. This method can achieve customized and intelligent control of baking processes based on the ecological environment and variety characteristics of specific production areas and tailored to the needs of cigarette industry enterprises, thereby improving the quality of tobacco baking and industrial availability.

[0004] The object of the present invention is achieved through the following technical solutions:

[0005] A customized and intelligent control method for tobacco leaf curing process, comprising: curing data collection, curing process portrait construction, curing process model customization, tobacco leaf status monitoring and curing process model comparison, and process adjustment instruction formation and automatic control.

[0006] Baking data collection: the baking data collection is to collect baking process data of no less than 10 batches for a specific tobacco producing area and variety; the collected data includes three types of data: ambient temperature in the baking room, wet-bulb temperature and tobacco leaf images.

[0007] Furthermore, the ambient temperature and wet-bulb temperature in the curing room are the data of the actual curing control shed (the curing room with rising airflow is the lower shed or middle shed, and the curing room with descending airflow is the upper shed or middle shed), and the tobacco leaf image is the middle shed data.

[0008] A baking process portrait is constructed, which includes "one point, three pictures, and one rate". Specifically, the data collected during the baking process are used to select several actual stable temperature points from a total of 10 stable temperature points, including ambient temperatures of 36°C, 38°C, 40°C, 42°C, 44°C, 46°C, 48°C or 50°C, 54°C, 60°C, 65 or 68°C. The duration, wet-bulb temperature, tobacco leaf image data and heating rate data from a certain stable temperature point to the next stable temperature point are summarized; the duration variation, wet-bulb temperature variation and tobacco leaf state variation ("three pictures") of each actual stable temperature point ("one point") are counted, and the heating rate ("one rate") between different stable temperature points is determined.

[0009] Furthermore, the tobacco leaf state variation at each actual stable temperature point can be the range of tobacco leaf RGB, Lab, HSV, YUL and other numerical values ​​extracted according to the color quantization model, or the range of tobacco leaf appearance state variation such as the yellowing degree and dryness degree extracted by the image recognition model established according to the artificial intelligence method, or the range of chemical components such as tobacco leaf starch, protein, reducing sugar, free amino acids established according to the artificial intelligence method.

[0010] The basic model of the baking process is customized based on the baking process portrait and the tobacco leaf quality requirements of the cigarette industry enterprises, and the duration variation and wet-bulb temperature variation of several actual stable temperature points are personalized.

[0011] Furthermore, the process customization methods combined with the tobacco leaf quality requirements of the cigarette industry enterprises include but are not limited to the following situations: (1) improving the degree of ripening after baking, extending the upper and lower limit time by 4h to 8h at the stable temperature points of 38℃ and 54℃, and increasing the wet bulb temperature by 0.5 to 1.5℃; (2) improving the brightness of the tobacco leaves after baking, shortening the upper and lower limit time by 4h to 8h at the stable temperature points of 50℃ and 54℃, and reducing the wet bulb temperature by 0.5 to 1.5℃.

[0012] The tobacco leaf monitoring and model comparison is the aforementioned customized baking process model. A camera is installed in the baking room to monitor the changes in the tobacco leaf state. When the duration of each stable temperature point reaches the lower limit of the stable temperature time variation, the tobacco leaf state is compared to see whether it reaches the aforementioned determined tobacco leaf state (that is, the tobacco leaf state variation at each actual stable temperature point can be the range of values ​​such as RGB or Lab or HSV or YUL of tobacco leaves extracted according to the color quantization model, or the range of changes in the tobacco leaf appearance state such as the yellowing degree and dryness degree extracted by the image recognition model established according to the artificial intelligence method, or the range of chemical components such as starch, protein, reducing sugar, free amino acids of tobacco leaves established according to the artificial intelligence method). If it is reached, a process adjustment instruction to raise the temperature to the next stable temperature point is generated. If it is not reached, the temperature is maintained and the tobacco leaf state is continuously compared. If the tobacco leaf state determined above is still not reached at the upper limit of the stable temperature time variation, the temperature is automatically raised to the next stable temperature point.

[0013] The process automatic control is a process adjustment command formed according to tobacco leaf status monitoring and model comparison, which is completed by the flue-curing room controller linking the flue-curing room heating device and dehumidification device.

[0014] Furthermore, process adjustment commands can be transmitted by an external control device equipped with computing power and deployed algorithms connected to the controller through a 485 interface, or the computing power and algorithms can be integrated into the baking room controller and completed independently by the baking room controller, or the computing power and algorithms can be deployed to the cloud platform and sent to the baking room controller through the 4G / 5G network.

[0015] The advantages of the present invention are: by collecting and analyzing the data of the baking process environment and tobacco leaf status of specific regions and varieties, a baking process portrait ("one point, three amplitudes, one rate") that conforms to the characteristics of the tobacco leaf producing area is constructed; based on the baking process portrait, the process parameters of the key temperature stabilization points (temperature stabilization time amplitude, wet bulb temperature amplitude) are personalized and customized to establish a customized baking process model based on the tobacco leaf quality requirements of the tobacco leaf production area and the tobacco leaf quality requirements of the tobacco leaf production area; by installing a camera in the baking room, the tobacco leaf status is monitored in real time and compared with the customized baking process model requirements, and the process adjustment instructions are automatically generated and automatically executed by the baking room controller, thereby completing the customization and intelligent control process of the tobacco leaf baking process. The method provided by the present invention can effectively solve the problems of weak pertinence and difficulty in implementation of customized production technology solutions, and realize customized and intelligent control of tobacco leaf baking. It can realize customized and intelligent control of baking processes based on the ecological environment and variety characteristics of specific production areas and for the needs of tobacco industry enterprises, thereby improving tobacco leaf baking quality and industrial availability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the customized and intelligent control method for the tobacco leaf baking process of the present invention. DETAILED DESCRIPTION

[0017] To more clearly and comprehensively illustrate the purpose and technical solutions of the present invention, the technical solutions of the present invention are clearly and completely described below using specific embodiments. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] Example 1

[0019] The embodiment of the present invention is a customized and intelligent control method for the tobacco leaf baking process of the Guangdong Meizhou Yunyan 87 variety.

[0020] Firstly, by installing Internet IoT communication modules and cameras in the flue-curing barn, the tobacco leaf curing process data was collected to establish a curing process portrait, including 9 stable temperature points at 38, 40, 42, 44, 46, 50, 54, 60, and 65°C, and the fluctuation range of the stable temperature time, wet-bulb temperature, tobacco leaf state, and heating rate at each stable temperature point.

[0021] Table 1 Portrait of tobacco leaf curing process in the central production area of ​​Meizhou, Guangdong

[0022]

[0023] Secondly, a baking process model was customized based on the quality requirement of a certain cigarette industry enterprise for the tobacco leaves produced in the Meizhou area, which "emphasizes the degree of ripening after baking."

[0024] Table 2 Customized baking process model for tobacco leaves in the central production area of ​​Meizhou, Guangdong

[0025]

[0026] Finally, cameras were installed in the flue-curing barn to monitor tobacco leaf image changes. After stabilizing at 38°C for 14 hours, the leaves were compared to see if they met the conditions specified in the flue-curing process model (Table 2) (70% to 80% yellowing and softening). Once they met the conditions, the temperature was raised at a rate of 0.5°C / hour to 40°C. If they continued to fall short, the temperature was raised again at a rate of 0.5°C / hour after 18 hours of stabilization. After stabilizing at 40°C for 16 hours, the leaves were compared to see if they met the conditions specified in the basic process model (Table 2) (70% to 80% yellowing and softening). If they fell short, the temperature was raised again at a rate of 0.33°C / hour to 42°C after 24 hours of stabilization. This process was repeated for the remaining stabilization points and temperature increases. All temperature increase commands were transmitted to the controller via a 485 interface via an external control device equipped with algorithms and computing power. The flue-curing barn controller automatically controlled the heating and dehumidification systems.

[0027] Example 2

[0028] The embodiment of the present invention is a customized and intelligent control method for the tobacco leaf baking process of the Yunyan 87 variety in Sanmenxia, ​​Henan Province.

[0029] Firstly, by installing Internet IoT communication modules and cameras in the flue-curing barn, the tobacco leaf curing process data was collected to establish a curing process portrait, including 10 stable temperature points at 36, 38, 40, 42, 44, 46, 50, 54, 60, and 68°C, and the stable temperature time range variation, wet-bulb temperature variation, tobacco leaf state variation, and heating rate of each stable temperature point.

[0030] Table 3 Portrait of tobacco leaf curing process in the central Sanmenxia production area of ​​Henan Province

[0031]

[0032] Secondly, a baking process model was customized based on the quality requirement of a cigarette industry enterprise for "improving the brightness of the color of tobacco leaves after baking" in the Sanmenxia production area.

[0033] Table 4 Customized baking process model for tobacco leaves in the central Sanmenxia production area of ​​Henan Province

[0034]

[0035]

[0036] Finally, a camera is installed in the flue-curing room to monitor the changes in the tobacco leaf image. The stable temperature time at the stable temperature point of 36°C reaches 4 hours. The tobacco leaf state is compared to see whether it reaches the tobacco leaf state range of the baking process model (Table 4) (50% to 60% yellow, leaves swollen and hardened). After reaching it, the temperature is raised to 38°C at a rate of 0.5°C / hour. If it continues to not reach it, the temperature is raised to 38°C at a rate of 0.5°C / hour after 6 hours of stable temperature. After the stable temperature of 38°C is reached for 18 hours, the tobacco leaf state is compared to see whether it reaches the tobacco leaf state range of the basic process model (Table 4) (70% to 80% yellow, leaves soft). After reaching the target temperature, the temperature is raised to 40°C at a rate of 0.50°C / hour. If the target temperature is not reached, the temperature is raised to 40°C at a rate of 0.5°C / hour after 24 hours of stabilization. After 18 hours of stabilization at 40°C, the tobacco leaves are compared to see if they have reached the target temperature range specified in the basic process model (Table 4) (yellow leaves with green veins at the base and collapsed leaves). If the target temperature is reached, the temperature is raised to 42°C at a rate of 0.50°C / hour. If the target temperature is not reached, the temperature is raised to 42°C at a rate of 0.5°C / hour after 24 hours of stabilization. The same process is repeated to complete the stabilization and temperature increase operations for the remaining stabilization points. All temperature increase commands are sent to the flue gas control device via the 4G network based on the cloud platform that deploys computing power and algorithms. The flue gas control device automatically controls the heating and dehumidification devices.

Claims

1. A customized and intelligent control method for tobacco leaf curing process, characterized in that: include: Baking data collection, baking process portrait construction, baking process model customization, tobacco leaf status monitoring and baking process model comparison, process adjustment instruction formation and automatic control.

2. The customized and intelligent control method for tobacco leaf curing process according to claim 1, characterized in that: The baking data collection link is for three types of data: ambient temperature in the baking room, wet-bulb temperature, and tobacco leaf image.

3. The customized and intelligent control method for tobacco leaf curing process according to claim 1, characterized in that: The baking process portrait construction link is to select several actual stable temperature points of the baking process of the region / variety from a total of 10 stable temperature points of 36°C, 38°C, 40°C, 42°C, 44°C, 46°C, 48°C or 50°C, 54°C, 60°C, 65 or 68°C according to the ambient temperature, wet-bulb temperature and tobacco leaf image data obtained in the baking data collection link, summarize the duration, wet-bulb temperature, tobacco leaf image data of each actual stable temperature point and the heating rate data from a certain stable temperature point to the next stable temperature point, count the duration variation, wet-bulb temperature variation and tobacco leaf state variation of each actual stable temperature point and determine the heating rate between different stable temperature points. The above is a baking process portrait that includes several stable temperature points called "one point", and the duration variation, wet-bulb temperature variation and tobacco leaf state variation of each temperature point called "three amplitudes", and the heating rate between different stable temperature points called "one rate".

4. The customized and intelligent control method for tobacco leaf curing process according to claim 3, characterized in that: The tobacco leaf state variation range at each actual steady temperature point can be the range of RGB, Lab, HSV or YUL values ​​of the tobacco leaves extracted according to the color quantification model, or the range of yellowing degree, dryness degree and appearance state of the tobacco leaves extracted by the image recognition model established by the artificial intelligence method, or the range of chemical composition of tobacco leaves starch, protein, reducing sugar and free amino acids established according to the artificial intelligence method.

5. The customized and intelligent control method for tobacco leaf curing process according to claim 1, characterized in that: The baking process model is customized based on the baking process portrait and the tobacco leaf quality requirements of the cigarette industry enterprises, and the duration variation and wet-bulb temperature variation of several actual stable temperature points are customized.

6. The customized and intelligent control method for tobacco leaf curing process according to claim 5, characterized in that: The duration variation and wet-bulb temperature variation of several actual temperature-stabilizing points are customized. The specific methods include but are not limited to the following situations: (1) To improve the degree of ripening after baking, the upper and lower limit time at the temperature-stabilizing points of 38℃ and 54℃ are extended by 4h~8h respectively, and the wet-bulb temperature is increased by 0.5~1.0℃; (2) To improve the brightness of the tobacco leaves after baking, the upper and lower limit time at the temperature-stabilizing points of 50℃ and 54℃ are shortened by 4h~8h respectively, and the wet-bulb temperature is reduced by 0.5~1.0℃.

7. The customized and intelligent control method for tobacco leaf curing process according to claim 1, characterized in that: The tobacco leaf state monitoring and model comparison is based on the baking process model determined according to claim 5. A camera is installed in the baking room to monitor the changes in the tobacco leaf image. When the duration of each stable temperature point reaches the lower limit of the stable temperature time variation, the tobacco leaf state is compared to see whether it reaches the tobacco leaf state determined in claim 4. If it reaches it, a process adjustment instruction is generated to raise the temperature to the next stable temperature point. If it does not reach it, the temperature is maintained and the tobacco leaf state is continuously compared. If the tobacco leaf state determined in claim 4 is still not reached at the upper limit of the stable temperature time variation, the temperature is automatically raised to the next stable temperature point.

8. The customized and intelligent control method for tobacco leaf curing process according to claim 1, characterized in that: The process adjustment instructions are automatically completed by the baking room controller linking the baking room heating device and the dehumidification device.

9. The customized and intelligent control method for tobacco leaf curing process according to claim 8, characterized in that: The process adjustment instructions are automatically completed by the baking room controller in conjunction with the baking room heating device and dehumidification device. The process adjustment commands can be transmitted by an external control device equipped with computing power and deployment algorithm connected to the baking room controller through the 485 interface, or the computing power and algorithm can be integrated into the baking room controller and completed independently by the baking room controller, or the computing power and algorithm can be deployed to the cloud platform and sent to the baking room controller via the 4G / 5G network.

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