CN114931230B - Process execution index analysis characterization method for tobacco leaf baking process - Google Patents

Abstract

The invention relates to a tobacco leaf baking process technological execution index analysis characterization method, which belongs to the baking process field, and comprises the steps of counting dry bulb temperature and wet bulb temperature of tobacco leaf baking stages, screening out an effective baking process according to the dry bulb temperature of the tobacco leaf, correspondingly determining different baking stages according to different baking temperatures, and finally determining the baking index of the tobacco leaf by utilizing the dry bulb temperature and the wet bulb temperature in each baking stage. According to the invention, a large amount of baking data can be rapidly separated and denoised in the screening one-time effective baking process, different baking stages can be correspondingly determined according to the baking temperatures corresponding to different baking processes, the baking indexes of different stages can be obtained, the determining process is simpler, and the efficiency is higher.

Description

A method for analyzing and characterizing process execution indicators of tobacco leaf baking process

Technical field

The invention relates to a tobacco leaf baking process process execution index analysis and characterization method, belonging to the field of baking technology.

Background technique

Tobacco leaf curing is a crucial link in the quality generation of flue-cured tobacco raw materials. The environmental changes in the curing room during the baking process are closely related to the intrinsic quality of tobacco leaves, and the baking time and changes in temperature and humidity in the curing room are important indicators for measuring the quality of baking.

With the development of Internet of Things technology, the application of Internet of Things in agriculture has become more and more extensive. By installing the Internet of Things module inside the baking room, the environmental changes during the baking process can be obtained, and then the baking quality can be controlled and judged. However, after collecting massive baking house IoT data, we face obstacles such as complex data cleaning and difficult mining. How to efficiently analyze and process the baking house IoT data is a solid foundation for the baking process to become intelligent. In the existing technology, baking data is analyzed and researched based on Internet of Things big data, but the intermediate analysis process mainly relies on empirical judgment and cannot be automated.

The Chinese patent document with application publication number CN1129141410A discloses an intelligent baking system based on Internet of Things data, but the application cannot automatically identify the baking stage. The Chinese patent document with application publication number CN1107719400A identifies the stages of the baking process based on image recognition, and then detects temperature and humidity changes through the Internet of Things module. There are color correction and model accuracy problems in the image recognition process, which often results in the inability to accurately measure the baking process. Indicators are accurately calculated.

Contents of the invention

The purpose of the present invention is to provide a method for analyzing and characterizing process execution indicators of a tobacco leaf baking process to solve the problem of being unable to accurately identify tobacco leaf baking stages and tobacco leaf baking indicators during the tobacco leaf baking process.

In order to achieve the above objects, the solution of the present invention includes:

A tobacco leaf baking process process execution index analysis and characterization method of the present invention includes the following steps:

1) Obtain the baking data during the tobacco leaf baking process. The baking data includes dry bulb temperature and wet bulb temperature, and extract the effective baking data for a single time according to the dry bulb temperature distribution;

2) Determine the starting point and end point of baking based on the dry bulb temperature in the single effective baking data;

3) Statistics of the dry bulb temperature in a single effective baking data, the time point when the dry bulb temperature is greater than the first set temperature for the first time is the end point of the yellowing period; the time point when the dry bulb temperature is greater than the second set temperature for the first time is The time point is the end point of the color fixation period, where the second set temperature is greater than the first set temperature, and the time interval between the starting point of baking and the end point of the yellowing period is the yellowing period; the end point of the yellowing period and The time interval between the endpoints of the fixation period is the fixation period; the time interval between the endpoints of the fixation period and the baking endpoint is the drying period;

4) Determine the baking index of the tobacco leaf based on the dry bulb temperature and/or wet bulb temperature at different baking stages of the tobacco leaf. The baking index includes at least one of the number of temperature drops and the wet bulb temperature state.

The beneficial effects of the above technical solution are: the tobacco leaf baking process process execution index analysis and characterization method provided by the present invention counts the dry bulb temperature and wet bulb temperature of the tobacco leaf baking stage, and selects an effective drying process according to the dry bulb temperature of the tobacco leaf. During the baking process, different baking stages are determined according to different baking temperatures. Finally, the dry bulb temperature and wet bulb temperature are used to determine the baking index of the tobacco leaves in each baking stage. The present invention can quickly separate and denoise a large amount of baking data during the screening of an effective baking process, can determine different baking stages according to the baking temperatures corresponding to different baking processes, and can obtain different Baking indicators at different stages, and the determination process is simpler and more efficient.

Further, the dry bulb temperature during the yellowing period is calculated, and the time point when the dry bulb temperature is greater than the third set temperature for the first time is the end point of the pre-yellowing stage; the time point when the dry bulb temperature is greater than the fourth set temperature for the first time is The time point is the end point of the low temperature stage of the yellowing period; the time point when the dry bulb temperature is greater than the fifth set temperature for the first time is the end point of the middle and low temperature stage of the yellowing stage; the time point when the dry bulb temperature is greater than the sixth set temperature for the first time is is the end point of the middle and high temperature stage of the yellowing period; the time point when the dry bulb temperature is greater than the seventh set temperature for the first time is the end point of the middle and high temperature stage of the yellowing period; among them, the value from the third set temperature to the seventh set temperature gradually increases. big;

The time interval between the starting point of the baking and the end point of the pre-yellowing stage is the pre-yellowing stage, and the time interval between the end point of the pre-yellowing stage and the end point of the low-temperature stage of the yellowing stage is the low-temperature stage of the yellowing stage. The time interval between the end point of the low temperature stage of the yellowing stage and the end point of the medium low temperature stage of the yellowing stage is the medium high temperature stage of the yellowing stage, and the time interval between the end point of the medium low temperature stage of the yellowing stage and the end point of the medium high temperature stage of the yellowing stage is the medium high temperature stage of the yellowing stage. stage, and the time interval between the end point of the high temperature stage in the yellowing stage and the end point of the yellowing stage is the high temperature stage of the yellowing stage.

Further, the dry-bulb temperature during the fixation period is calculated, and the time point when the dry-bulb temperature is greater than the eighth set temperature for the first time is the end point of the low-temperature stage of the fixation period; the time when the dry-bulb temperature is greater than the ninth set temperature for the first time is The time point is the end of the middle temperature stage of the fixation period; among them, the ninth set temperature is greater than the eighth set temperature;

The time interval between the end point of the yellowing period and the end point of the low-temperature stage of the fixation period is the low-temperature stage of the fixation period, and the time interval between the end point of the low-temperature stage of the fixation period and the end point of the medium-temperature stage of the fixation period is the medium-temperature stage of the fixation period. stage, and the time interval between the end point of the medium temperature stage of the fixation period and the end point of the fixation period is the high temperature stage of the fixation period.

Further, the dry bulb temperature during the drying period is calculated, and the time point when the dry bulb temperature is greater than the tenth set temperature for the first time is the end point of the low temperature stage of the drying period; the end point of the fixation period is the same as the end point of the low temperature stage of the drying period. The time interval between them is the low-temperature stage of the tendon drying period, and the time interval between the end point of the low-temperature stage of the tendon drying stage and the baking end point is the high-temperature stage of the tendon drying stage.

The beneficial effects of the above technical solution are: according to the baking temperatures of different baking stages, the yellowing period, color fixing period and drying period of the tobacco leaf baking process can be divided in more detail, so that the characterization of the tobacco leaf baking stage can be more detailed. for accuracy.

Further, when in the yellowing period, the current dry bulb temperature is subtracted from the adjacent previous dry bulb temperature to obtain the first temperature difference. The number of times the first temperature difference is less than the first set difference is the yellowing period. number of temperature drops.

Further, when in the fixing period, the current dry bulb temperature is subtracted from the adjacent last dry bulb temperature to obtain the second temperature difference. The number of times the second temperature difference is less than the second set difference is the fixing period. number of temperature drops.

Further, when in the drying period, the current dry bulb temperature is subtracted from the adjacent last dry bulb temperature to obtain a third temperature difference. The number of times the third temperature difference is less than the third set difference is considered to be drying. The number of temperature drops per period.

Furthermore, when it is in the gluten drying period, the number of temperature drops within the first set time period before the baking end point is not counted as the number of temperature drops in the gluten drying period.

Further, the wet-bulb temperature state includes a wet-bulb water-deficient state and a wet-bulb normal state; the wet-bulb temperature during the fixation period is statistically calculated. If the wet-bulb temperature is greater than the first set wet-bulb temperature, the wet-bulb temperature is the constant state. The wet-bulb dehydration state during the coloring period; the wet-bulb temperature during the drying-out period is calculated. If the wet-bulb temperature is greater than the second set wet-bulb temperature, the wet-bulb temperature is the wet-bulb dehydration state during the drying-out period.

Further, the dry bulb temperature in the statistics of a single effective baking data is the average dry bulb temperature within the second set time range; the wet bulb temperature in the statistics of a single effective baking data is the average dry bulb temperature in the third set time range. Average wet bulb temperature.

The beneficial effects of the above technical solution are: using the average dry bulb temperature and the average wet bulb temperature as reference values for dividing the baking stages and determining the baking indicators, effectively avoiding interference with the data and ensuring the accuracy of the baking stages and baking indicators. .

Description of the drawings

Figure 1 is a flow chart of a method for analyzing and characterizing process execution indicators of the tobacco leaf baking process of the present invention;

Figure 2 is the original single tobacco leaf curing data chart from a certain place;

Figure 3 is a graph of baking data extracted between the baking starting point and the baking end point using the present invention;

Figure 4 is a graph showing the baking data of a certain place including multiple baking data;

Figure 5 is a single baking data chart with baking number 1;

Figure 6 is a single baking data chart with baking number 2;

Figure 7 is a single baking data chart with baking number 3;

Figure 8 is a single baking data chart with baking number 4;

Figure 9 is a diagram of different baking stages of a single baking data with baking number 1;

Figure 10 is a diagram of different baking stages of a single baking data with baking number 2;

Figure 11 is a diagram of different baking stages of a single baking data with baking number 3;

Figure 12 is a diagram of different baking stages of the single baking data with baking number 4;

Figure 13 is the wet bulb temperature distribution diagram of the single baking data with baking number 1;

Figure 14 is the wet bulb temperature distribution diagram of the single baking data with baking number 2;

Figure 15 is the wet bulb temperature distribution diagram of the single baking data with baking number 3;

Figure 16 is the wet bulb temperature distribution diagram of the single baking data with baking number 4;

Figure 17 is a distribution diagram of the number of temperature drops for a single baking data with baking number 1;

Figure 18 is a distribution diagram of the number of temperature drops for a single baking data with baking number 2;

Figure 19 is a distribution diagram of the number of temperature drops for a single baking data with baking number 3;

Figure 20 is a distribution diagram of the number of temperature drops for a single baking data with baking number 4;.

Detailed ways

The present invention will be described in further detail below with reference to the accompanying drawings.

Example:

The invention provides a tobacco leaf baking process process execution index analysis and characterization method. First, the frequency and range of the dry bulb temperature data of the Internet of Things are used to identify the baking data and record the effective baking data; then the effective baking data is subjected to noise processing. Make the baking data more stable and smooth; then based on the temperature range and duration of baking, identify the baking stages of the effective baking data after denoising, and construct the yellowing period, color fixation period and drying period of the tobacco leaves; finally By analyzing the dry and wet bulb temperature data at different baking stages, the dry and wet bulb temperature ranges and median values in different periods were calculated, and the number of temperature drops and water shortages in the baking room were recorded. The method of the present invention can be used to identify the baking curve formed by the baking data of the baking room, denoise the characteristics of the baking curve, extract the temperature and humidity changes during the baking process based on the characteristics of the baking curve, and calculate the number of temperature drops. and wet bulb temperature status and other baking indicators.

The flow chart of the tobacco leaf baking process process execution index analysis and characterization method of the present invention is shown in Figure 1, which includes the following steps:

1) Obtain effective baking data of tobacco leaves.

During the tobacco leaf baking process, the baking data within a baking cycle are obtained by the dry and wet bulb temperature sensors. The recording frequency of the dry and wet bulb temperature sensors is about 5 to 8 minutes/time. Use the resample function in the Python third-party library Pandas to sample the data during the baking process to obtain the tobacco leaf baking data.

Obtain the dry bulb temperature for each hour during a baking cycle, use the dry bulb temperature for each hour to calculate the average dry bulb temperature within an hour, and determine whether the average dry bulb temperature during a baking cycle is greater than 54.4°C. data. If the average dry bulb temperature in a baking cycle does not have data greater than 54.4°C, or the number of dry bulb temperature data records in a baking cycle is less than 100 times, it means that the data of the baking cycle is invalid. The baking data does not exist and the reference value needs to be eliminated.

2) Select the baking cycle with reference value within multiple baking cycles. In one baking cycle, the tobacco leaves will be baked multiple times, so there will be multiple times of heating and cooling in one baking cycle. process. If the total duration of a baking cycle is less than 4 days, the baking cycle is an invalid baking cycle. After eliminating invalid baking cycles, select valid baking data from the remaining baking cycles with reference value. The specific selection method is: use the time point when the first dry bulb temperature is greater than 54.4°C as the starting time point. The time point when the dry bulb temperature is greater than 54.4℃ for the first time after the recording time interval is greater than 4 days is used as the dividing point. The time point when the dry bulb temperature is greater than 54.4℃ for the last time after the dividing point is used as the end time point. From the starting time point to the end time The baking data within the point is valid baking data. However, the number of dry-bulb temperature records in the effective baking data must be greater than or equal to 100 times, and the number of missing dry-bulb temperatures cannot reach 10% of the total number of dry-bulb temperature records. From the starting time point to the ending time point, if the number of dry-bulb temperature records is less than 100, or the number of missing dry-bulb temperatures accounts for 10% of the total number of dry-bulb temperature records, then the baking data in this section is still considered invalid. Baking data, determine the single effective baking data based on the effective baking data.

Use the shift function to shift the time points of the valid baking data, and calculate the time interval between the time points before and after the shift. If there is still baking data with a dry bulb temperature greater than 54.4°C and a recording interval greater than 4 days, It is considered that multiple valid baking data may be recorded in this section of baking data; if there is no baking data with a dry bulb temperature greater than 54.4°C and a recording interval greater than 4 days, it is considered that only a single baking data is recorded in this section of baking data. Valid baking data.

In the single effective baking data, it is judged whether there is baking data with dry bulb temperature less than or equal to 42.4℃ and greater than 54.4℃ in the baking data. If it does not exist, it is further determined that the effective baking data in this section is invalid data; if it exists , then the baking data of less than or equal to 42.4℃ in the effective baking data of this section will be used as the baking front-end data.

3) Identify the baking stage for a single effective baking data.

Use the resample function in Python to calculate the average value of the dry bulb temperature baking data within 2 hours of the baking front-end data, then use the shift function to calculate the change range of the average value of adjacent baking data, and use the resample function to calculate the variation of the baking data within 8 hours. The sum of the changes in the average value. Count the number of dry-bulb temperature data before the time point corresponding to the maximum value of the average change amplitude of the baking data. If the number of dry-bulb temperature data is less than or equal to 3, then the number of dry-bulb temperature data corresponding to the minimum value of the dry-bulb temperature in the baking front-end data will be counted. The time point is used as the starting point of baking; if the number of dry-bulb temperature data is greater than 3, the time point corresponding to the first dry-bulb temperature data that is greater than 80% of the maximum variation range of the average value of the baking data will be used before that time point. The time point corresponding to the minimum value of the dry bulb temperature data in 8 hours is used as the starting point of baking.

If there is baking data with a dry bulb temperature greater than 60°C in the single effective baking data, the time point corresponding to the last dry bulb temperature greater than 60°C will be used as the baking end point; if there is no dry ball in the single effective baking data For data with a temperature greater than 60°C, the time point corresponding to the last dry bulb temperature greater than 54.4°C is used as the baking end point. The time interval between the baking start point and the baking end point is the total baking time, and the baking data between the baking start point and the baking end point is the final baking data.

The final baking data is used to determine the length of the yellowing period, color fixation period and drying period of the tobacco leaves. Calculate the average of the 2-h dry-bulb temperature in the final baking data, and use the first point in time when the dry-bulb temperature is greater than 42.4°C in the 2 hours when the average is greater than 42.4°C as the end point of the yellowing period, then the starting point of the baking and the yellowing period The baking data between the end points is the baking data of the yellowing period, and the time interval between the starting point of baking and the end point of the yellowing period is the length of the yellowing period. Calculate the average of the 2-h dry-bulb temperature in the final baking data, and use the first point in time when the dry-bulb temperature is greater than 54.4°C in 2 hours when the average is greater than 54.4°C as the end of the fixation period. Then the end of the yellowing period is the same as the fixation. The baking data between the end points of the period is the baking data of the fixation period, and the time interval between the end point of the yellowing period and the end of the fixation period is the length of the fixation period. The baking data between the end of the fixation period and the end of baking is the baking data of the drying period, and the time interval between the end of the fixing period and the end of baking is the length of the drying period.

4) Calculate baking indicators at different baking stages.

In the baking data during the yellowing period, calculate the average dry bulb temperature within 1 hour. The time point when the dry bulb temperature is greater than 35.4℃ for the first time is the end point of the pre-yellowing stage, the time point when the dry bulb temperature is greater than 37.4℃ for the first time is the end point of the low temperature stage of the yellowing stage, and the time point when the dry bulb temperature is greater than 38.4℃ is the end point of the yellowing stage. The time point of ℃ is used as the end point of the medium-low temperature stage of the yellowing period, and the time point when the dry bulb temperature is greater than 40.4℃ for the first time is the end point of the medium-high temperature stage of the yellowing stage.

The data between the starting point of baking and the end point of the pre-yellowing stage is the data of the pre-yellowing stage, and the time interval between the starting point of baking and the end point of the pre-yellowing stage is the length of the pre-yellowing stage. The data between the end of the pre-yellowing stage and the end of the low-temperature stage of the yellowing stage is the low-temperature stage data of the yellowing stage, and the time interval between the end of the pre-yellowing stage and the end of the low-temperature stage of the yellowing stage is the length of the low-temperature stage of the yellowing stage. The data between the end point of the low temperature stage of the yellowing period and the end point of the medium and low temperature stage of the yellowing stage is the data of the medium and low temperature stage of the yellowing stage. The time interval between the end point of the low temperature stage and the end point of the medium and low temperature stage of the yellowing stage is the medium and low temperature stage of the yellowing stage. duration. The data between the end point of the medium low temperature stage in the yellowing period and the end point of the medium high temperature stage in the yellowing stage is the data of the medium high temperature stage in the yellowing stage. The time interval between the end point of the medium low temperature stage in the yellowing stage and the end point of the medium high temperature stage in the yellowing stage is the medium high temperature stage in the yellowing stage. duration, and calculate the median wet-bulb temperature during the middle and high-temperature stages of the yellowing period. The data between the end point of the medium-high temperature stage and the end point of the yellowing period is the data of the high-temperature stage of the yellowing stage, and the time interval between the end point of the medium-high temperature stage and the end point of the yellowing stage is the duration of the high-temperature stage of the yellowing stage. After determining the duration of each stage of the yellowing period, the median value of the wet-bulb temperature at each stage of the yellowing stage is calculated. As another embodiment, the average or variance of the wet-bulb temperature at each stage of the yellowing stage can also be calculated.

In the baking data during the fixation period, calculate the average dry bulb temperature within 1 hour. The time point when the average dry bulb temperature is greater than 46.4℃ for the first time within 1 hour is the end point of the low temperature stage of the fixation period, and the time point when the dry bulb temperature is greater than 49.4℃ for the first time is the end point of the medium temperature stage of the fixation period.

The data between the end of the yellowing period and the end of the low-temperature stage of the fixing period is the data of the low-temperature stage of the fixing period. The time interval between the end of the yellowing period and the end of the low-temperature stage of the fixing period is the length of the low-temperature stage of the fixing period. The data between the end of the low-temperature stage of the fixation period and the end of the medium-temperature stage of the fixation period is the data of the medium-temperature stage of the fixation period. The time interval between the end of the low-temperature stage of the fixation period and the end of the medium-temperature stage of the fixation period is the length of the medium-temperature stage of the fixation period. . The data between the end of the medium temperature stage of the fixation period and the end of the fixation period is the data of the high temperature stage of the fixation period. The time interval between the end of the medium temperature stage of the fixation period and the end of the fixation period is the length of the high temperature stage of the fixation period. After determining the duration of each stage of the fixation period, the median value of the wet bulb temperature at each stage of the fixation period is calculated. As another embodiment, the average value or variance of the wet bulb temperature at each stage of the fixation period can also be calculated.

In the baking data during the drying period, calculate the average dry bulb temperature within 1 hour. The time point when the dry bulb temperature is greater than 60.4℃ for the first time is regarded as the end point of the low temperature stage of the tendon drying period.

The data between the end of the fixation period and the end of the low-temperature stage of the tendon drying period is the data of the low-temperature stage of the tendon drying period. The time interval between the end of the color-fixing period and the end of the low-temperature stage of the tendon drying stage is the length of the low-temperature stage of the tendon drying period. The data between the end of the low-temperature phase of the tendon drying period and the end of baking is the data of the high-temperature stage of the tendon drying period. The time interval between the end of the low-temperature stage of the tendon drying period and the end of baking is the length of the high-temperature stage of the tendon drying period. After determining the duration of each stage of the tendon drying period, the median value of the wet bulb temperature at each stage of the tendon drying stage is calculated respectively. As another embodiment, the average value or variance of the wet bulb temperature at each stage of the tendon drying stage can also be calculated.

After determining the different stages of tobacco leaf baking, count the number of temperature drops in the yellowing stage, color fixing stage and drying stage. During the baking process of tobacco leaves, when the dry bulb temperature drops by 3°C within 2 hours, it is considered to be a temperature drop. Use the resample function to calculate the baking data of the yellowing period and the fixation period, calculate the average value of the dry bulb temperature for 0.2 hours, calculate the difference between the dry bulb temperatures at adjacent time points, and use the resample function to calculate the difference between the average values for 2 hours. and count the number of data in which the sum of the differences between the average dry bulb temperatures is less than -3°C. This number of data is the number of temperature drops corresponding to the baking stage. When counting the number of temperature drops during the drying period, if the dry bulb temperature difference is less than -3℃ 3 hours before the baking end point, the data with the dry bulb temperature difference less than -3℃ 3 hours before the baking end point will not be counted as the number of temperature drops. .

In addition, it is also necessary to calculate the wet bulb temperature status during the fixation period and the drying period. During the baking process, the lack of water in the wet bulb during the color fixation and drying phases will cause the wet bulb temperature to increase significantly. Under normal circumstances, the wet bulb temperature is always below 45°C. During the fixation period and the drying period, the wet bulb temperature is greater than 45°C, which means the wet bulb is short of water. Therefore, calculate the average value of the wet bulb temperature for 1 hour. If the wet bulb temperature is greater than the data of 45°C, the wet bulb temperature within the corresponding time range of the wet bulb temperature is the wet bulb dehydration; if the wet bulb temperature is less than the data of 45°C , then the wet-bulb temperature within the time range corresponding to the wet-bulb temperature is wet-bulb normal.

To sum up, when determining the tobacco leaf baking stage, in order to avoid the interference of the data of a single sampling point and affecting the judgment of the baking stage, the dry bulb temperature and wet bulb temperature used in the present invention are both the average within a certain period of time. value, as other embodiments, the variance within a certain time period can also be used to determine the baking stage. Moreover, in the baking process of different tobacco leaves, different baking stages are specifically divided at different temperatures. The temperatures that separate each baking stage in the present invention are obtained through human experience. When different types of tobacco leaves are baked, the The baking temperature will vary and can be adjusted according to actual conditions. In addition, when calculating the average value of wet-bulb temperature and dry-bulb temperature in a certain short period of time, the average value of dry-bulb temperature and wet-bulb temperature for the corresponding duration can be determined based on the length of the baking stage.

The present invention is used to bake tobacco leaves in a certain place. As shown in Figure 2, the original single tobacco leaf baking data in a certain place is extracted from the original single tobacco leaf baking data. Baking data, as shown in Figure 3.

The tobacco leaf curing in a certain place contains multiple curing data, as shown in Figure 4. The single curing data is extracted from the multiple curing data, as shown in Figure 5, Figure 6, Figure 7 and Figure 8. The present invention is used to determine the baking stage for each single baking data as shown in Table 1, where the baking number of the corresponding baking data in Figure 5 is 1, and the baking number of the corresponding baking data in Figure 6 is 2 , the baking number of the corresponding baking data in Figure 6 is 3, the baking number of the corresponding baking data in Figure 7 is 3, and the baking number of the corresponding baking data in Figure 8 is 4.

Table 1 Baking duration at different stages during the baking process

The baking stages corresponding to each single baking data in Table 1 are shown in Figure 9, Figure 10, Figure 11 and Figure 12. The baking stages in the figure from left to right are the yellowing stage, the color fixing stage and the drying stage. Expect. Based on four different baking data, the present invention is used to calculate the baking duration of different baking stages as shown in Table 2, and the median wet bulb temperature is shown in Table 3.

Table 2 Baking duration at different stages in the baking process

Table 3 Median values of wet bulb temperature at different periods and stages during the baking process

The wet-bulb states at different baking stages of four single effective baking data are respectively counted as shown in Table 4. The specific situations are shown in Figures 13, 14, 15 and 16.

Table 4 Corresponding wet bulb states at different stages during the baking process

The number of temperature drops in different baking stages of the four single effective baking data is calculated as shown in Table 5. The specific situation is shown in Figure 17, Figure 18, Figure 19 and Figure 20.

Table 5 Temperature loss statistics at different periods during the baking process

Claims (10)

1. A method for analyzing and characterizing process execution indicators of tobacco leaf baking process, which is characterized in that it includes the following steps: 1) Obtain the baking data during the tobacco leaf baking process. The baking data includes dry bulb temperature and wet bulb temperature. Extract the effective baking data for a single time based on the dry bulb temperature distribution; perform a single effective baking data based on the dry bulb temperature distribution. The process of extracting effective baking data includes the steps of selecting effective baking data. The specific selection method is: within the effective baking cycle, the time point when the first dry bulb temperature is greater than the first set temperature is used as the starting time point. , the time point when the dry bulb temperature is greater than the first set temperature for the first time after the recording time interval is greater than 4 days is used as the dividing point, and the time point when the dry bulb temperature is greater than the first set temperature for the last time after the dividing point is taken as the end time point. The baking data from the starting time point to the ending time point is valid baking data; 2) Determine the baking starting point and baking end point based on the dry bulb temperature in the single effective baking data; 3) Calculate the dry bulb temperature between the baking start point and the baking end point in the single effective baking data. The time point when the dry bulb temperature is greater than the first set temperature for the first time is the end point of the yellowing period; the dry bulb temperature is The time point when the temperature is greater than the second set temperature for the first time is the end point of the fixation period, wherein the second set temperature is greater than the first set temperature; the time interval between the starting point of baking and the end point of the yellowing period is the time point of the yellowing period. period; the time interval between the end point of the yellowing period and the end point of the fixation period is the fixation period; the time interval between the end point of the fixation period and the baking end point is the drying period; 4) The number of temperature drops is determined based on the dry bulb temperature of the tobacco leaves at different baking stages, and the wet bulb temperature state is determined based on the wet bulb temperature of the tobacco leaves at different baking stages; the number of temperature drops and the wet bulb temperature state are both baking indicators of the tobacco leaves. ; The wet-bulb temperature state includes a wet-bulb dehydration state and a normal wet-bulb state. 2. The tobacco leaf baking process process execution index analysis and characterization method according to claim 1, characterized in that the dry bulb temperature during the yellowing period is counted, and the time point when the dry bulb temperature is greater than the third set temperature for the first time is used. It is the end point of the pre-yellowing stage; the time point when the dry bulb temperature is greater than the fourth set temperature for the first time is the end point of the low temperature stage of the yellowing stage; the time point when the dry bulb temperature is greater than the fifth set temperature for the first time is yellowing. The end point of the middle low temperature stage; the time point when the dry bulb temperature is greater than the sixth set temperature for the first time is the end point of the middle high temperature stage of the yellowing stage; the time point when the dry bulb temperature is greater than the seventh set temperature for the first time is the high temperature stage of the yellowing stage The end point of the stage; wherein, the third set temperature to the seventh set temperature gradually increase in value; The time interval between the starting point of the baking and the end point of the pre-yellowing stage is the pre-yellowing stage, and the time interval between the end point of the pre-yellowing stage and the end point of the low-temperature stage of the yellowing stage is the low-temperature stage of the yellowing stage. The time interval between the end point of the low temperature stage of the yellowing stage and the end point of the medium low temperature stage of the yellowing stage is the medium low temperature stage of the yellowing stage, and the time interval between the end point of the medium low temperature stage of the yellowing stage and the end point of the medium high temperature stage of the yellowing stage is the medium high temperature of the yellowing stage. stage, and the time interval between the end point of the high temperature stage in the yellowing stage and the end point of the yellowing stage is the high temperature stage of the yellowing stage. 3. The tobacco leaf baking process process execution index analysis and characterization method according to claim 1, characterized in that the dry bulb temperature during the color fixation period is calculated based on the time point when the dry bulb temperature is greater than the eighth set temperature for the first time. is the end point of the low-temperature stage of the fixation period; the time point when the dry bulb temperature is greater than the ninth set temperature for the first time is the end point of the mid-temperature stage of the fixation period; where the ninth set temperature is greater than the eighth set temperature; The time interval between the end point of the yellowing period and the end point of the low-temperature stage of the fixation period is the low-temperature stage of the fixation period, and the time interval between the end point of the low-temperature stage of the fixation period and the end point of the medium-temperature stage of the fixation period is the medium-temperature stage of the fixation period. stage, and the time interval between the end point of the medium temperature stage of the fixation period and the end point of the fixation period is the high temperature stage of the fixation period. 4. The tobacco leaf baking process process execution index analysis and characterization method according to claim 1, characterized in that the dry bulb temperature during the drying period is calculated as the time point when the dry bulb temperature is greater than the tenth set temperature for the first time. is the end point of the low-temperature stage of the tendon drying stage; the time interval between the end point of the fixation period and the end point of the low-temperature stage of the tendon drying stage is the low-temperature stage of the tendon drying stage, and the time interval between the end point of the low-temperature stage of the tendon drying stage and the baking end point It is the high-temperature stage of the muscle drying period. 5. The tobacco leaf baking process process execution index analysis and characterization method according to claim 2, characterized in that, when in the yellowing stage, the current dry bulb temperature is subtracted from the adjacent last dry bulb temperature to obtain the first temperature. The number of times the first temperature difference is less than the first set difference is the number of temperature drops in the yellowing period. 6. The tobacco leaf baking process process execution index analysis and characterization method according to claim 3, characterized in that, when in the fixation period, the current dry bulb temperature is subtracted from the adjacent last dry bulb temperature to obtain the second temperature. The number of times the second temperature difference is less than the second set difference is the number of temperature drops during the fixation period. 7. The tobacco leaf baking process process execution index analysis and characterization method according to claim 4, characterized in that, when in the drying period, the current dry bulb temperature is subtracted from the adjacent last dry bulb temperature to obtain the third temperature. difference, the number of times the third temperature difference is less than the third set difference is the number of temperature drops during the drying period. 8. The tobacco leaf baking process process execution index analysis and characterization method according to claim 7, characterized in that when it is in the drying period, the number of temperature drops within the first set time period before the baking end point is not counted as the drying period. Number of temperature drops. 9. The tobacco leaf baking process process execution index analysis and characterization method according to claim 1, characterized in that the wet bulb temperature during the color fixation period is statistically calculated. If the wet bulb temperature is greater than the first set wet bulb temperature, then the The wet bulb temperature is the wet bulb water shortage state during the fixation period; the wet bulb temperature during the dry tendon period is calculated. If the wet bulb temperature is greater than the second set wet bulb temperature, the wet bulb temperature is the wet bulb during the dry tendon period. Water shortage state. 10. The tobacco leaf baking process process execution index analysis and characterization method according to any one of claims 1 to 9, characterized in that the dry bulb temperature in the statistical single effective baking data is within the second set time range. Average dry-bulb temperature; count the wet-bulb temperature in the single effective baking data, and use the statistical wet-bulb temperature in the single effective baking data as the average wet-bulb temperature within the third set time range.