阅读说明：本技术 低碳数字化烟叶仓储养护方法及系统 (Low-carbon digital tobacco leaf storage and maintenance method and system ) 是由 王春录 范甜甜 陈兆麟 肖光伟 陈浩 王法 方玉强 谢莉 黄闫江 于 2021-09-25 设计创作，主要内容包括：本申请涉及烟叶养护的领域,尤其是涉及一种低碳数字化烟叶仓储养护方法及系统。低碳数字化烟叶仓储养护方法包括：获取烟叶种类信息数据、养护周期数据；调用数据库,获取该种烟叶在该养护周期下所有不同工艺的参数以及,不同工艺最终获得的成品品质得分；筛选成品品质得分最高的设定比例的工艺参数拟合或选择成品品质得分最高的工艺参数作为实施工艺参数。获取烟叶的种类信息和需要的养护周期数据后,调用数据库中所有该烟叶在该养护周期内的工艺数据,筛选出成品品质最高得分最高的一定比例的工艺进行拟合获得实施工艺参数,通过数字化控制使烟叶养护周期和品质处于可控状态,并达到低碳环保的效果。(The application relates to the field of tobacco leaf curing, in particular to a low-carbon digital tobacco leaf storage curing method and system. The low-carbon digital tobacco leaf storage and maintenance method comprises the following steps: acquiring tobacco leaf type information data and maintenance period data; calling a database to obtain parameters of all different processes of the tobacco leaves in the curing period and quality scores of finished products finally obtained by the different processes; and screening the process parameter fitting with the set proportion with the highest finished product quality score or selecting the process parameter with the highest finished product quality score as an implementation process parameter. After the type information of the tobacco leaves and the required maintenance period data are obtained, all process data of the tobacco leaves in the maintenance period in the database are called, a certain proportion of processes with the highest finished product quality score are screened out for fitting to obtain implementation process parameters, the tobacco leaf maintenance period and the quality are in a controllable state through digital control, and the effects of low carbon and environmental protection are achieved.)

1. The low-carbon digital tobacco leaf storage and maintenance method is characterized by comprising the following steps:

acquiring tobacco leaf type information data and maintenance period data;

calling a database to obtain parameters of all different processes of the tobacco leaves in the curing period and quality scores of finished products finally obtained by the different processes;

and screening the process parameter fitting with the set proportion with the highest finished product quality score or selecting the process parameter with the highest finished product quality score as an implementation process parameter.

2. The low-carbon digital tobacco leaf warehousing and curing method as claimed in claim 1, further comprising:

acquiring temperature data information of implementation process parameters and temperature data information of all warehouse years, and fitting the temperature data of each warehouse year according to daily average temperature to form a temperature curve of the whole year;

and integrating the absolute value of the temperature curve of each warehouse in the whole year and the temperature data difference value of the implementation process parameters to obtain a temperature control energy consumption reference value, and selecting the warehouse with the lowest temperature control energy consumption reference value as an implementation warehouse.

3. The low-carbon digital tobacco leaf warehousing and curing method as claimed in claim 2, wherein implementation process parameters and tobacco leaf quality scores obtained by implementation are recorded into a database.

4. The low-carbon digital tobacco leaf storage and maintenance method as claimed in claim 1, wherein the specific fitting manner is that the temperature, humidity and oxygen concentration of the first hypoxia stage of the screened process are weighted according to the quality scores and then respectively averaged, the temperature, humidity and oxygen concentration of the second hyperoxic stage of the screened process are weighted according to the quality scores and then respectively averaged, and the temperature, humidity and oxygen concentration of the third hypoxia stage of the screened process are weighted according to the quality scores and then respectively averaged.

5. The low-carbon digital tobacco leaf storage and maintenance method according to claim 1, wherein the specific fitting manner is to respectively average the temperature, humidity and oxygen concentration of the first hypoxia stage of the screened process, respectively average the temperature, humidity and oxygen concentration of the second hypoxia stage of the screened process, and respectively average the temperature, humidity and oxygen concentration of the third hypoxia stage of the screened process.

6. The low-carbon digital tobacco leaf warehousing maintenance method as claimed in claim 1, wherein the tobacco leaf identification module is used for obtaining the data information of the type, the producing area, the grade and the moisture of the tobacco leaves, and when the database is called, the parameters of various different processes of the same tobacco leaves in the maintenance period and the quality scores of finished products finally obtained by the different processes are obtained.

7. A low carbon digital tobacco leaf warehousing system for use with the method of any one of claims 1-6, comprising: the database unit is used for storing parameters of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes;

and a comparison screening unit for screening the process with the highest set proportion of the finished product quality score.

8. The low-carbon digital tobacco leaf warehousing system of claim 7, further comprising: and the process parameter fitting unit is used for fitting various different process parameters to obtain implementation process parameters.

9. The low-carbon digital tobacco leaf warehousing system of claim 8, further comprising: and the warehouse selection unit is used for integrating absolute values of temperature data of all warehouses over the year and temperature data difference values of implementation process parameters to obtain a temperature control energy consumption reference value, and selecting the warehouse with the lowest temperature control energy consumption reference value as the implementation warehouse.

Technical Field

The application relates to the field of tobacco leaf curing, in particular to a low-carbon digital tobacco leaf storage curing method and system.

Background

In China, the tobacco curing insect pest control is mainly carried out by means of aluminum phosphide fumigation insect killing or chemical control spraying method carried out in the peripheral environment, warehouse empty warehouse, environment comprehensive treatment and the like, and the tobacco mellowing curing is mainly carried out by means of natural mellowing; the tobacco leaves are stored in a sealed way by mainly adopting methods such as air-conditioned tobacco leaf curing and the like, and a more obvious effect is obtained.

However, the curing period and the quality of the tobacco leaves at present are uncontrollable to a certain extent, and the process adopted by each tobacco leaf in any curing period cannot be determined. For example, if the normal process cycle for curing and alcoholizing a particular leaf is 3 years, then the process is determined to be acceptable and result in a high quality leaf. However, if the user wishes to be able to produce the finished product within 1 year due to some factor such as the reimbursement period, there is no standard data on the process of the tobacco leaves to achieve the highest possible quality within a 1 year period. Therefore, the applicant intends to solve the problem and to control the curing cycle and quality of the tobacco leaves as a whole.

Disclosure of Invention

In order to obtain a process for curing high-quality tobacco leaves in any period, the application provides a low-carbon digital tobacco leaf storage curing method.

In a first aspect, the low-carbon digital tobacco leaf storage and maintenance method provided by the application adopts the following technical scheme:

the low-carbon digital tobacco leaf storage and maintenance method is characterized by comprising the following steps:

acquiring tobacco leaf type information data and maintenance period data;

calling a database to obtain parameters of all different processes of the tobacco leaves in the curing period and quality scores of finished products finally obtained by the different processes;

and screening the process parameter fitting with the set proportion with the highest finished product quality score or selecting the process parameter with the highest finished product quality score as an implementation process parameter.

By adopting the technical scheme, after the type information of the tobacco leaves and the required maintenance period data are obtained, all the process data of the tobacco leaves in the maintenance period in the database are called, the process with the highest finished product quality score in a certain proportion is screened out to be fitted to obtain the implementation process parameters, or the process with the highest finished product quality score is directly selected as the implementation process parameters. The data obtained by using the process can further increase the database content so as to continuously improve the subsequent implemented process, and the tobacco leaf curing period and the quality are in a controllable state through digital control.

Preferably, temperature data information of implementation process parameters and temperature data information of all warehouse years are obtained, and the temperature data of each warehouse year is fitted according to daily average temperature to form a temperature curve of the whole year; and integrating the absolute value of the temperature curve of each warehouse in the whole year and the temperature data difference value of the implementation process parameters to obtain a temperature control energy consumption reference value, and selecting the warehouse with the lowest temperature control energy consumption reference value as an implementation warehouse.

By adopting the technical scheme, the absolute value integral is obtained after the temperature data of the implementation process parameters and the temperature data of each warehouse in the past year are subjected to difference calculation, the energy consumption of the process implemented by the warehouse is evaluated according to the temperature control energy consumption reference value obtained through calculation, the warehouse with the lowest relative energy consumption is selected as the implementation warehouse, the maintenance energy consumption is reduced, and the effects of low carbon and environmental protection are achieved.

Preferably, the implementation process parameters and the tobacco leaf quality scores obtained by implementation are recorded into a database.

By adopting the technical scheme, the implementation process parameters and the obtained tobacco quality scores are recorded into the database, data are increased, and the accuracy of the subsequent data analysis and adoption process is improved.

Preferably, the specific fitting method is to weight the temperature, humidity and oxygen concentration of the first hypoxia stage of the screened process according to the quality scores and then respectively calculate the average, weight the temperature, humidity and oxygen concentration of the second hypoxia stage of the screened process according to the quality scores and then respectively calculate the average, weight the temperature, humidity and oxygen concentration of the third hypoxia stage of the screened process according to the quality scores and then respectively calculate the average.

By adopting the technical scheme, the temperature, humidity and oxygen concentration data of the first stage, the second stage and the third stage of the process are respectively fitted to form new implementation process parameters. And the quality score weighting is increased during fitting, so that the tobacco leaves can be more effectively closed to the theoretical optimal process under a specific curing period.

Preferably, the specific fitting method is to respectively average the temperature, humidity and oxygen concentration of the first hypoxia stage of the screened process, respectively average the temperature, humidity and oxygen concentration of the second hyperoxic stage of the screened process, and respectively average the temperature, humidity and oxygen concentration of the third hypoxia stage of the screened process.

By adopting the technical scheme, the temperature, humidity and oxygen concentration data of the first stage, the second stage and the third stage of the process are respectively fitted to form new implementation process parameters.

Preferably, the type, producing area, grade and water data information of the tobacco leaves are obtained through the tobacco leaf identification module, and when the database is called, parameters of various different processes of the same tobacco leaves in the curing period and quality scores of finished products finally obtained by the different processes are obtained.

By adopting the technical scheme, the information of the type, the producing area, the grade and the water data of the tobacco leaves is obtained through the tobacco leaf identification module, and the implementation process formed by analyzing the process data of the same tobacco leaves is closer to the theoretical optimal value.

In a second aspect, the present application provides a low-carbon digital tobacco leaf warehousing system used in the method, which adopts the following technical scheme:

the low-carbon digital tobacco leaf warehousing system comprises: the database unit is used for storing parameters of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes;

and a comparison screening unit for screening the process with the highest set proportion of the finished product quality score.

By adopting the technical scheme, the specific data are called through the database unit, and the process of obtaining the finished product with high quality score through screening is carried out for subsequent data analysis.

Preferably, the system further comprises a process parameter fitting unit for fitting a plurality of different process parameters to obtain implementation process parameters.

By adopting the technical scheme, a plurality of different process parameters are fitted to obtain implementation process parameters as actually used process parameters.

Preferably, the system further comprises a warehouse selection unit, the absolute value of the difference between the temperature data of each warehouse over the year and the temperature data of the implementation process parameters is taken and integrated to obtain a temperature control energy consumption reference value, and the warehouse with the lowest temperature control energy consumption reference value is selected as the implementation warehouse.

By adopting the technical scheme, the warehouse with the lowest energy consumption of matched implementation process parameters is selected through the warehouse selection unit, and the energy consumption of maintenance is reduced.

In summary, the present application includes at least one of the following beneficial technical effects:

1. after the type information of the tobacco leaves and the required maintenance period data are obtained, all process data of the tobacco leaves in the maintenance period in the database are called, a certain proportion of processes with the highest finished product quality score are screened out for fitting to obtain implementation process parameters, the data obtained after the process can further increase the database content to continuously improve the subsequent implementation processes, and the maintenance period and the quality of the tobacco leaves are in a controllable state through digital control.

2. The absolute value integral is obtained after the temperature data of the implementation process parameters and the temperature data of each warehouse over the year are subtracted, the energy consumption of the warehouse for implementing the process is evaluated according to the temperature control energy consumption reference value obtained through calculation, the warehouse with the lowest relative energy consumption is selected as the implementation warehouse, the maintenance energy consumption is reduced, and the effects of low carbon and environmental protection are achieved.

3. And respectively fitting the temperature, humidity and oxygen concentration data of the first stage, the second stage and the third stage of the process to form new implementation process parameters, and increasing the quality score weighting during fitting so as to more quickly approach the theoretical optimal process of the tobacco leaves in a specific curing period.

Detailed Description

The embodiment of the application discloses a low-carbon digital tobacco leaf storage and maintenance method and system.

Example one

The low-carbon digital tobacco leaf storage and maintenance method comprises the following steps:

step one, calling a database, wherein the database comprises parameters (process parameters refer to temperature, humidity and oxygen concentration parameters) of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes.

For example, the quality of finished products obtained by curing certain tobacco leaves for one year under different temperature, humidity and oxygen concentration parameters (the sample amount is more than one thousand) is counted, and the grading method of the quality of the finished products can refer to GB 5606.4-2005, and can also refer to other grading methods such as YCT 138-.

The specific scoring mode is as follows:

each appraiser scores the tobacco leaves from the angles of fragrance, oil, fragrance, fullness, fineness, sufficiency, roughness, coordination, miscellaneous gas, irritation, aftertaste, purity, cleanness, peculiar smell, mildew and the like, and adds the scores to serve as the appraiser score, the upper limit of the score of each angle is determined by the influence of the angle on the quality of the tobacco leaves, and the actual upper limit of the score can be set by referring to the national standard scoring method or according to the actual requirement. And averaging the scores of a plurality of evaluators to obtain the finished product quality score of the tobacco leaf.

And step two, setting the type of the tobacco leaves and the maintenance period. And acquiring parameters of all processes of the tobacco leaves of the same type in a specific curing period and a finished product quality score correspondingly obtained by each process. The screening score ranks the top ten percent of the processes.

And step three, fitting the screened process parameters. The specific fitting mode is that the temperature, the humidity and the oxygen concentration of the first hypoxia stages of all the processes are weighted according to the quality scores and then are respectively averaged, the temperature, the humidity and the oxygen concentration of the second hyperoxic stages of all the processes are weighted according to the quality scores and then are respectively averaged, and the temperature, the humidity and the oxygen concentration of the third hypoxia stages of all the processes are weighted according to the quality scores and then are respectively averaged.

The obtained process parameters are used as implementation process parameters (the implementation process parameters refer to parameters actually used in the tobacco curing process).

And step four, acquiring temperature data information of the implementation process parameters and acquiring temperature data information of each warehouse in the past year. The historical temperature data for each warehouse was fitted to the daily average temperature to form a whole year temperature curve.

And fifthly, integrating the absolute value of the temperature curve of the whole year of each warehouse (the warehouses can be different storage areas in different regions and can also be different storage areas in the same building) and the temperature data difference value of the implementation process parameters (the temperature data of the implementation process parameters are put into the same coordinate system by taking the process starting implementation time as the starting time and the temperature data curve of the warehouse in the past year), and obtaining the area value formed between the temperature data curve of each warehouse in the past year and the temperature data curve of the implementation process parameters, namely the temperature control energy consumption reference value. And selecting a warehouse with the lowest reference value of temperature control energy consumption as an implementation warehouse (the implementation warehouse refers to a warehouse actually used for tobacco leaf curing).

And step six, recording the implementation process parameters and the tobacco leaf quality scores obtained by implementation into a database.

Example two

The low-carbon digital tobacco leaf storage and maintenance method comprises the following steps:

step one, calling a database, wherein the database comprises parameters of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes.

And step two, setting the type of the tobacco leaves and the maintenance period. And acquiring parameters of all processes of the tobacco leaves of the same type in a specific curing period and a finished product quality score correspondingly obtained by each process. The screening score ranks the top ten percent of the processes.

And step three, fitting the screened process parameters. The specific fitting mode is that the temperature, the humidity and the oxygen concentration of the first hypoxia stage of all the processes are respectively averaged, the temperature, the humidity and the oxygen concentration of the second hypoxia stage of all the processes are respectively averaged, and the temperature, the humidity and the oxygen concentration of the third hypoxia stage of all the processes are respectively averaged.

The obtained process parameters are used as implementation process parameters.

And step four, acquiring temperature data information of the implementation process parameters and acquiring temperature data information of each warehouse in the past year. The historical temperature data for each warehouse was fitted to the daily average temperature to form a whole year temperature curve.

And fifthly, integrating absolute values of the temperature curves of all the warehouses in the whole year and the temperature data difference values of the implementation process parameters to obtain area values formed between the temperature data curves of all the warehouses in the years and the temperature data curves of the implementation process parameters, namely the reference values of temperature control energy consumption. And selecting the warehouse with the lowest reference value of temperature control energy consumption as an implementation warehouse.

And step six, recording the implementation process parameters and the tobacco leaf quality scores obtained by implementation into a database.

EXAMPLE III

The tobacco leaf recognition module is trained and molded through a large number of different types of tobacco leaf quality photo data, the type, producing area, grade and moisture data information of the tobacco leaves is obtained after the photos of the input tobacco leaves are shot, and the type, producing area, grade and moisture data of the tobacco leaves can also be manually input.

The low-carbon digital tobacco leaf storage and maintenance method comprises the following steps:

the method comprises the steps of firstly, obtaining maintenance period information, and obtaining the data information of the type, the producing area, the grade and the water content of the tobacco leaves through a tobacco leaf identification module.

And step two, calling a database to obtain parameters of various processes of the tobacco leaves with the type, the producing area, the grade and the moisture in the curing period and quality scores of finished products finally obtained by the different processes. The screening score ranks the top ten percent of the processes.

And step three, fitting the screened process parameters. The specific fitting mode is that the temperature, the humidity and the oxygen concentration of the first hypoxia stages of all the processes are weighted according to the quality scores and then are respectively averaged, the temperature, the humidity and the oxygen concentration of the second hyperoxic stages of all the processes are weighted according to the quality scores and then are respectively averaged, and the temperature, the humidity and the oxygen concentration of the third hypoxia stages of all the processes are weighted according to the quality scores and then are respectively averaged.

The obtained process parameters are used as implementation process parameters.

And step four, acquiring temperature data information of the implementation process parameters and acquiring temperature data information of each warehouse in the past year. The historical temperature data for each warehouse was fitted to the daily average temperature to form a whole year temperature curve.

And fifthly, integrating absolute values of the temperature curves of all the warehouses in the whole year and the temperature data difference values of the implementation process parameters to obtain area values formed between the temperature data curves of all the warehouses in the years and the temperature data curves of the implementation process parameters, namely the reference values of temperature control energy consumption. And selecting the warehouse with the lowest reference value of temperature control energy consumption as an implementation warehouse.

Example four

The low-carbon digital tobacco leaf storage and maintenance method comprises the following steps:

step one, calling a database, wherein the database comprises parameters of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes.

And step two, setting the type of the tobacco leaves and the maintenance period. And acquiring parameters of all processes of the tobacco leaves of the same type in a specific curing period and a finished product quality score correspondingly obtained by each process. And selecting the process parameter with the highest quality score as the implementation process parameter.

And step three, acquiring temperature data information of the implementation process parameters and acquiring temperature data information of each warehouse in the past year. The historical temperature data for each warehouse was fitted to the daily average temperature to form a whole year temperature curve.

And step four, integrating absolute values of the temperature curves of all the warehouses in the whole year and the temperature data difference values of the implementation process parameters to obtain area values formed between the temperature data curves of all the warehouses in the years and the temperature data curves of the implementation process parameters, namely the reference values of temperature control energy consumption. And selecting the warehouse with the lowest reference value of temperature control energy consumption as an implementation warehouse.

EXAMPLE five

The low carbon digital tobacco leaf storage and maintenance system comprises:

and the database unit is used for storing parameters of various different processes of each tobacco leaf in a specific curing period and quality scores of finished products finally obtained by the different processes.

And the comparison screening unit is used for comparing and obtaining ten processes before the ranking of the scores.

And the process parameter fitting unit is used for fitting various different process parameters to obtain implementation process parameters.

And the warehouse selection unit is used for integrating absolute values of temperature data of all warehouses over the year and temperature data difference values of implementation process parameters to obtain a temperature control energy consumption reference value, and selecting the warehouse with the lowest temperature control energy consumption reference value as the implementation warehouse.

The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.