Abnormality monitoring method and system based on tobacco leaf curing process

Abstract

The invention relates to the technical field of tobacco leaf curing data identification, and particularly discloses an abnormity monitoring method and system based on a tobacco leaf curing process, and the method comprises the steps: analyzing the initial state of tobacco leaves, obtaining the maturity grade of the tobacco leaves through comparison, determining a tobacco leaf curing defined evaluation value data set, and analyzing the state of a tobacco leaf curing environment, according to the method, the problems that a traditional tobacco leaf curing abnormity monitoring method is not high in accuracy degree, insufficient in automation degree and large in tobacco leaf quality fluctuation are solved, it can be ensured that each batch of tobacco leaves are processed under the optimal condition, and the tobacco leaf curing quality is improved. Unified processing standards and a monitoring system help to maintain quality consistency in the production process, excessive or insufficient baking can be avoided, image, chemical and equipment states in the baking process can be monitored, deviation can be quickly recognized and adjusted, and quality problem expansion is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco leaf baking data recognition, and in particular to an abnormality monitoring method and system based on a tobacco leaf baking process. Background Art

[0002] Tobacco leaf baking is a key step in tobacco processing, which directly affects the quality and flavor of the final product. The baking process requires precise control of temperature, humidity and time to ensure that the chemical composition of the tobacco leaves is properly converted. Abnormal baking conditions may lead to inconsistent tobacco leaf quality and affect the taste and aroma of tobacco products. Developing an effective abnormality monitoring system is the key to ensuring product quality and market competitiveness. Tobacco leaf baking is an energy and resource intensive process. Any improvement in baking efficiency can significantly reduce production costs. Abnormal monitoring can help timely detect and correct production deviations, reduce energy waste, and avoid raw material losses, thereby improving overall production efficiency. With the development of sensing technology, data analysis and artificial intelligence, automation and intelligence of the tobacco leaf baking process have become possible. Using these advanced technologies for abnormal monitoring can not only improve the accuracy and response speed of monitoring, but also achieve more advanced predictive maintenance and optimization decisions.

[0003] At present, there are still some shortcomings in the research on an abnormality monitoring method based on the tobacco leaf baking process. Specifically, the traditional tobacco leaf baking abnormality monitoring method is not accurate enough and the degree of automation is insufficient, resulting in large fluctuations in tobacco leaf quality and failure to ensure the quality consistency of each batch of tobacco leaves. The low-precision monitoring method may lead to failure to timely detect abnormalities in production, such as improper temperature and humidity control, resulting in over-baking or under-baking of tobacco leaves, which not only wastes raw materials but also increases energy consumption because the equipment may need to run longer to correct these problems. When the abnormality monitoring system cannot be automated or responds slowly, more manual intervention is required to check and adjust the production process, which not only slows down production but also increases labor costs. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and system for monitoring abnormalities during tobacco leaf baking, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides a method for monitoring abnormalities in a tobacco leaf baking process, comprising the following steps: analyzing the initial state of the tobacco leaves, and obtaining the maturity level of the tobacco leaves by comparison; determining a tobacco leaf baking definition evaluation value data set based on the maturity level of the tobacco leaves, wherein the tobacco leaf baking definition evaluation value data set specifically includes an image recognition definition evaluation value, a chemical definition evaluation value, and an equipment status definition evaluation value; analyzing the tobacco leaf baking environment state, and determining a tobacco leaf baking scheme in combination with the maturity level of the tobacco leaves; baking the tobacco leaves based on the tobacco leaf baking scheme, analyzing the tobacco leaf baking image recognition state, and judging whether there is an abnormality in the tobacco leaf baking image recognition state in combination with the image recognition definition evaluation value; baking the tobacco leaves based on the tobacco leaf baking scheme, analyzing the tobacco leaf baking chemical state, and judging whether there is an abnormality in the tobacco leaf baking chemical state in combination with the chemical definition evaluation value; baking the tobacco leaves based on the tobacco leaf baking scheme, analyzing the tobacco leaf baking equipment state, and judging whether there is an abnormality in the tobacco leaf baking equipment state in combination with the equipment status definition evaluation value.

[0006] As a further method, the initial state of tobacco leaves is analyzed and the maturity grade of tobacco leaves is obtained by comparison. The specific analysis process is: obtaining a tobacco leaf initial state data set, the tobacco leaf initial state data set specifically includes the initial average moisture content of tobacco leaves, the initial average weight of tobacco leaves, and the initial average nicotine content of tobacco leaves; based on the obtained tobacco leaf initial state data set, a comprehensive analysis is performed to obtain tobacco leaf initial state characteristic values, and the tobacco leaf initial state characteristic values ​​are used as an analysis basis for obtaining the tobacco leaf maturity grade by comparison; the tobacco leaf initial state characteristic values ​​are compared with the tobacco leaf maturity grades corresponding to the tobacco leaf initial state characteristic values ​​stored in the database, to obtain the tobacco leaf maturity grade corresponding to the tobacco leaf initial state characteristic values.

[0007] As a further method, a tobacco leaf curing definition evaluation value data set is determined based on the tobacco leaf maturity grade. The specific analysis process is: the tobacco leaf maturity grade is stored as a specified label, and the specified label is compared with the tobacco leaf curing definition evaluation value data set corresponding to each specified label stored in the database to obtain the tobacco leaf curing definition evaluation value data set corresponding to the specified label.

[0008] As a further method, the tobacco leaf baking environment status is analyzed, and the tobacco leaf baking plan is determined in combination with the tobacco leaf maturity level. The specific analysis process is: obtaining a tobacco leaf baking environment status data set, the tobacco leaf baking environment status data set specifically includes the tobacco leaf baking environment temperature, the tobacco leaf baking environment humidity, and the tobacco leaf baking environment air flow velocity; the tobacco leaf baking environment temperature, the tobacco leaf baking environment humidity, the tobacco leaf baking environment air flow velocity, and the tobacco leaf maturity level are stored as designated labels, and the designated label is compared with the tobacco leaf baking plans corresponding to each designated label stored in the database to obtain the tobacco leaf baking plan corresponding to the designated label.

[0009] As a further method, it is determined whether there is an abnormality in the tobacco leaf baking image recognition state, and the specific analysis process is: obtain a tobacco leaf baking image recognition state data set, which specifically includes the number of tobacco leaves broken by baking, the number of tobacco leaves deformed by baking, and the number of abnormal tobacco leaf baking texture density; based on the acquired tobacco leaf baking image recognition state data set, a comprehensive analysis is performed to obtain an image recognition state evaluation value, and the image recognition state evaluation value is used as an analysis basis for determining whether there is an abnormality in the tobacco leaf baking image recognition state; the image recognition state evaluation value is compared with the image recognition boundary evaluation value; if the image recognition state evaluation value is not lower than the image recognition boundary evaluation value, then there is no abnormality in the tobacco leaf baking image recognition state corresponding to the image recognition state evaluation value; if the image recognition state evaluation value is lower than the image recognition boundary evaluation value, then there is an abnormality in the tobacco leaf baking image recognition state corresponding to the image recognition state evaluation value, and an alarm is issued for tobacco leaf baking with abnormal image recognition state.

[0010] As a further method, the image recognition state evaluation value, the specific analysis process is:

[0011]

[0012] Where γ is the image recognition state evaluation value, sl is the number of tobacco leaf breakages, bx is the number of tobacco leaf deformations, yc is the number of abnormal texture density of tobacco leaf baking, ε1 is the compensation factor of sl, ε2 is the compensation factor of bx, ε3 is the compensation factor of yc, and e is a natural constant.

[0013] As a further method, it is determined whether there is any abnormality in the chemical state of tobacco leaf baking, and the specific analysis process is: obtain a tobacco leaf baking chemical state data set, the tobacco leaf baking chemical state data set specifically includes the absolute value of the difference between the tobacco leaf volatile organic matter content and the reference volatile organic matter content, the absolute value of the difference between the tobacco leaf nicotine and the reference nicotine, and the absolute value of the difference between the tobacco leaf pH value and the reference pH value; based on the obtained tobacco leaf baking chemical state data set, a comprehensive analysis is performed to obtain a chemical state evaluation value, and the chemical state evaluation value is used as an analysis basis for determining whether there is any abnormality in the tobacco leaf baking chemical state; the chemical state evaluation value is compared with the chemical definition evaluation value; if the chemical state evaluation value is not lower than the chemical definition evaluation value, then the tobacco leaf baking chemical state corresponding to the chemical state evaluation value does not have any abnormality; if the chemical state evaluation value is lower than the chemical definition evaluation value, then the tobacco leaf baking chemical state corresponding to the chemical state evaluation value has an abnormality, and an alarm is issued for tobacco leaf baking with abnormal chemical state.

[0014] As a further method, the chemical state evaluation value, the specific analysis process is:

[0015]

[0016] In the formula, is the chemical state assessment value, hf is the absolute value of the difference between the volatile organic compound content of tobacco leaves and the reference volatile organic compound content, ngd is the absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine, PH is the absolute value of the difference between the pH value of tobacco leaves and the reference pH value, σ1 is the compensation factor of the set hf, σ2 is the compensation factor of the set ngd, and σ3 is the compensation factor of the set PH.

[0017] As a further method, it is determined whether there is an abnormality in the state of the tobacco leaf baking equipment. The specific analysis process is: obtain a tobacco leaf baking equipment state data set, the tobacco leaf baking equipment state data set specifically includes the number of abnormal temperature fluctuations of the tobacco leaf baking equipment, the absolute value of the difference between the actual baking time of the tobacco leaf baking equipment and the set baking time, and the smoke concentration generated by the tobacco leaf baking equipment; based on the acquired tobacco leaf baking equipment state data set, a comprehensive analysis is performed to obtain a tobacco leaf baking equipment state evaluation value, and the tobacco leaf baking equipment state evaluation value is used as an analysis basis for determining whether there is an abnormality in the state of the tobacco leaf baking equipment; the tobacco leaf baking equipment state evaluation value is compared with the equipment state definition evaluation value; if the tobacco leaf baking equipment state evaluation value is not lower than the equipment state definition evaluation value, then there is no abnormality in the tobacco leaf baking equipment state corresponding to the tobacco leaf baking equipment state evaluation value; if the tobacco leaf baking equipment state evaluation value is lower than the equipment state definition evaluation value, then there is an abnormality in the tobacco leaf baking equipment state corresponding to the tobacco leaf baking equipment state evaluation value, and an alarm is issued for tobacco baking with abnormal equipment state.

[0018] The second aspect of the present invention provides an abnormality monitoring system based on the tobacco leaf baking process, including a tobacco leaf maturity level comparison module, a boundary evaluation value data set determination module, a tobacco leaf baking scheme determination module, an image recognition state abnormality judgment module, a chemical state abnormality judgment module and an equipment state abnormality judgment module, wherein: the tobacco leaf maturity level comparison module is used to analyze the initial state of the tobacco leaf and compare to obtain the tobacco leaf maturity level; the boundary evaluation value data set determination module is used to determine the tobacco leaf baking boundary evaluation value data set based on the tobacco leaf maturity level, and the tobacco leaf baking boundary evaluation value data set specifically includes image recognition boundary evaluation value, chemical boundary evaluation value and equipment state boundary evaluation value; the tobacco leaf baking scheme determination module is used to determine the tobacco leaf baking environment The state is analyzed, and the tobacco leaf baking plan is determined in combination with the tobacco leaf maturity level; the image recognition state abnormality judgment module is used to bake the tobacco leaves based on the tobacco leaf baking plan, analyze the tobacco leaf baking image recognition state, and judge whether there is an abnormality in the tobacco leaf baking image recognition state in combination with the image recognition definition evaluation value; the chemical state abnormality judgment module is used to bake the tobacco leaves based on the tobacco leaf baking plan, analyze the tobacco leaf baking chemical state, and judge whether there is an abnormality in the tobacco leaf baking chemical state in combination with the chemical definition evaluation value; the equipment state abnormality judgment module is used to bake the tobacco leaves based on the tobacco leaf baking plan, analyze the state of the tobacco leaf baking equipment, and judge whether there is an abnormality in the tobacco leaf baking equipment state in combination with the equipment state definition evaluation value.

[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0020] (1) The present invention provides a method and system for monitoring abnormalities during tobacco leaf baking. Baking parameters are precisely set based on maturity levels to ensure that each batch of tobacco leaves is processed under optimal conditions, thereby optimizing the aroma, color and taste of the tobacco leaves. Unified processing standards and monitoring systems help maintain quality consistency during the production process. By precisely controlling baking parameters, over- or under-baking can be avoided, thereby reducing the waste of raw materials and energy. By monitoring the image, chemistry and equipment status during the baking process, deviations can be quickly identified and adjusted to avoid the expansion of quality problems.

[0021] (2) The present invention determines the tobacco leaf baking definition evaluation value data set through the tobacco leaf maturity grade, and can accurately adjust the baking conditions to ensure that each batch of tobacco leaves is processed under the optimal conditions. This method helps to maximize the conversion of beneficial chemical components in tobacco leaves and minimize undesirable components, thereby improving the overall quality of tobacco leaves. Appropriate baking evaluation settings can reduce tobacco leaf losses caused by improper processing (such as over-baking or under-baking). Reducing the waste of raw materials not only saves costs, but also improves the overall efficiency and profitability of production.

[0022] (3) The present invention analyzes the state of the tobacco leaf baking environment, determines the tobacco leaf baking plan in combination with the tobacco leaf maturity level, and adjusts the baking environment according to the characteristics of tobacco leaves of different maturity levels. This can ensure that each batch of tobacco leaves is processed under the most suitable conditions, thereby maximizing the chemical and physical quality of the tobacco leaves. Systematically analyzing and controlling the baking process can reduce the quality differences between batches and ensure the consistency and predictability of the products. The precise baking process reduces the loss of tobacco leaves caused by improper baking, such as carbonization of tobacco leaves caused by over-baking or insufficient baking that affects the quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0024] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0025] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0026] Figure 3 It is a three-dimensional image of the change of the characteristic value of the initial state of the tobacco leaves along with the initial average nicotine content of the tobacco leaves and the set compensation factor of the initial average nicotine content of the tobacco leaves.

[0027] Figure 4 This is an image of the change in the initial state characteristic values ​​of the tobacco leaves as the average initial nicotine content of the tobacco leaves changes. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] Reference Figure 1 As shown, the first aspect of the present invention provides a method for monitoring abnormalities during tobacco leaf baking, comprising: analyzing the initial state of the tobacco leaves and obtaining the maturity level of the tobacco leaves by comparison.

[0030] The specific analysis process is as follows: obtaining a tobacco leaf initial state data set, which specifically includes the initial average moisture content of tobacco leaves, the initial average weight of tobacco leaves, and the initial average nicotine content of tobacco leaves; based on the obtained tobacco leaf initial state data set, a comprehensive analysis is performed to obtain tobacco leaf initial state characteristic values, which are used as an analysis basis for comparing and obtaining tobacco leaf maturity levels; comparing tobacco leaf initial state characteristic values ​​with tobacco leaf maturity levels corresponding to each tobacco leaf initial state characteristic value stored in a database, to obtain tobacco leaf maturity levels corresponding to the tobacco leaf initial state characteristic value.

[0031] In a specific embodiment, the characteristic value of the initial state of tobacco leaves is specifically analyzed as follows:

[0032]

[0033] Wherein, β is the characteristic value of the initial state of tobacco leaves, hs is the initial average moisture content of tobacco leaves, zl is the initial average weight of tobacco leaves, ng is the initial average nicotine content of tobacco leaves, μ1 is the compensation factor of the set hs, μ2 is the compensation factor of the set zl, and μ3 is the compensation factor of the set ng.

[0034] It needs to be explained that the above-mentioned characteristic values ​​of the initial state of tobacco leaves are calculated through the initial average moisture content of tobacco leaves, the initial average weight of tobacco leaves, and the initial average nicotine content of tobacco leaves. HS, ZL, and NG are normalized. Analysis of moisture content, weight or nicotine content alone may not fully reflect the overall quality of tobacco leaves. By combining these parameters into an initial state characteristic value, the overall state and quality of tobacco leaves can be more comprehensively evaluated. By combining multiple indicators, the error caused by fluctuations in a single indicator can be reduced, and the accuracy of determining the state of tobacco leaves can be improved. The key characteristics of tobacco leaves, such as maturity and baking adaptability, can be more accurately judged. According to the initial state characteristic values ​​of tobacco leaves, the baking and subsequent processing techniques can be better customized. Different characteristic values ​​can correspond to different baking temperature curves and time settings, thereby optimizing the baking effect.

[0035] like Figure 3 As shown in FIG. 1 , it is a three-dimensional image of the change of the characteristic value of the initial state of tobacco leaves with the average initial nicotine content of tobacco leaves and the compensation factor of the set average initial nicotine content of tobacco leaves. As the average initial nicotine content of tobacco leaves and the compensation factor of the set average initial nicotine content of tobacco leaves increase, the characteristic value of the initial state of tobacco leaves also increases, as shown in FIG. Figure 4As shown, it is an image of the change of the initial state characteristic value of tobacco leaves with the initial average nicotine content of tobacco leaves, where the x-axis represents the initial nicotine content of tobacco leaves, and the y-axis represents the initial state characteristic value of tobacco leaves, which can help to intuitively understand how the initial nicotine content of tobacco leaves affects the initial state characteristic value of tobacco leaves. The larger the initial nicotine content of tobacco leaves, the larger the initial state characteristic value of tobacco leaves. As the initial average nicotine content of tobacco leaves increases, the influence of the initial nicotine content of tobacco leaves on the initial state characteristic value of tobacco leaves gradually weakens. The initial average moisture content of tobacco leaves is set to 20, the initial average weight of tobacco leaves is set to 2, the compensation factor of the initial average moisture content of tobacco leaves is set to 0.3, the compensation factor of the initial average weight of tobacco leaves is set to 0.3, and the compensation factor of the initial average nicotine content of tobacco leaves is set to 0.5. Only the initial average nicotine content of tobacco leaves is changed. The example values ​​of the initial average nicotine content of tobacco leaves are as follows:

[0036] Table 1: Example values ​​of the average initial nicotine content of tobacco leaves in the initial state characteristic values ​​of tobacco leaves

[0037] n hs(%) zl(gram) ng(%) <![CDATA[μ1]]> <![CDATA[μ2]]> <![CDATA[μ3]]> β 1 20 2 2 0.3 0.3 0.5 1.820781 2 20 2 4 0.3 0.3 0.5 2.885870 3 20 2 5 0.3 0.3 0.5 3.290798

[0038] It should be explained that the compensation factors of hs, zl, ng set above are obtained from the database. According to the historical data, a mapping set of the historically measured initial average moisture content of tobacco leaves, the initial average weight of tobacco leaves, the initial average nicotine content of tobacco leaves and the compensation factors of hs, zl, ng is established to obtain the compensation factors of hs, zl, ng corresponding to the current hs, zl, ng.

[0039] It should be noted that ε1, ε2, ε3, σ1, σ2, σ3, τ1, τ2, and τ3 mentioned below are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained based on the current data.

[0040] It needs to be explained that the above-mentioned average initial moisture content of tobacco leaves refers to the proportion of moisture contained in tobacco leaves when they are picked or initially processed, usually expressed as a percentage by mass, that is, the mass of moisture in the tobacco leaves accounts for the percentage of the total mass of the tobacco leaves. The moisture content is estimated by measuring the capacitance value of the tobacco leaves. The average initial weight of tobacco leaves refers to the average mass of a single tobacco leaf when it is picked or initially processed, which can reflect the growth of the tobacco leaves and whether the appropriate time for harvesting has been reached. It is obtained based on sorting and weighing equipment. The average initial nicotine content of tobacco leaves refers to the proportion of nicotine contained in tobacco leaves. Nicotine content is an important chemical indicator that determines the quality and grade of tobacco leaves. Nicotine is accurately determined using liquid chromatography technology.

[0041] It needs to be explained that the moisture content of the above-mentioned tobacco leaves directly affects their weight. When the moisture content of the tobacco leaves is high, the weight of the tobacco leaves will increase accordingly. Since moisture is an important component of weight, changes in moisture content will cause fluctuations in the weight of the tobacco leaves. The initial average weight of the tobacco leaves includes the influence of moisture. Tobacco leaves with a higher moisture content usually lead to a lower relative concentration of nicotine. Moisture increases the overall mass of the tobacco leaves, which makes the nicotine content (concentration) per unit mass relatively reduced. The initial weight of the tobacco leaves reflects the overall mass of the tobacco leaves, including the sum of components such as moisture, fiber, sugar and nicotine. The nicotine content indicates the proportion of nicotine therein. Under certain conditions, tobacco leaves with a heavier initial weight may contain a higher total amount of nicotine.

[0042] It should be explained that the above-mentioned analysis of the characteristic values ​​of the initial state of tobacco leaves (such as moisture content, weight, and nicotine content) can more accurately judge the maturity of tobacco leaves, avoid the errors that may be caused by judging based on experience or appearance alone, and improve the scientificity and consistency of the judgment. By comparing the characteristic values ​​of the initial state of tobacco leaves with the characteristic values ​​of known maturity levels in the database, abnormal conditions in the maturation process of tobacco leaves can be discovered earlier, so that timely measures can be taken to ensure the quality of the final product. With accurate assessment of the initial state, the production process can better classify and process tobacco leaves of different grades, reduce unnecessary processing steps, and improve overall production efficiency. The analysis model established using the data set can standardize the process of judging the maturity of tobacco leaves, which helps different batches of tobacco leaves maintain consistent quality standards under different production conditions.

[0043] Based on the maturity level of tobacco leaves, a tobacco leaf baking definition assessment value data set is determined. The tobacco leaf baking definition assessment value data set specifically includes image recognition definition assessment value, chemical definition assessment value and equipment status definition assessment value.

[0044] The specific analysis process is: storing the tobacco leaf maturity level as a designated label, comparing the designated label with the tobacco leaf baking definition evaluation value data set corresponding to each designated label stored in the database, and obtaining the tobacco leaf baking definition evaluation value data set corresponding to the designated label.

[0045] In a specific embodiment, by comparing the tobacco leaf maturity grade label with the baking definition evaluation value, the baking scheme that best matches the maturity grade can be selected, thereby ensuring that each batch of tobacco leaves can obtain the best processing effect during the baking process. The use of unified labels and evaluation data can maintain consistent baking effects in tobacco leaves from different batches and sources, thereby improving the quality consistency of the final product. Systematic comparison of labels and evaluation data can quickly determine baking parameters, shorten production preparation time, and improve overall production efficiency. Accurate matching of baking parameters avoids excessive or insufficient baking, and reduces energy consumption and material waste.

[0046] Analyze the tobacco leaf curing environment status and determine the tobacco leaf curing plan based on the tobacco leaf maturity level.

[0047] The specific analysis process is as follows: obtaining a tobacco leaf baking environment status data set, which specifically includes a tobacco leaf baking environment temperature, a tobacco leaf baking environment humidity, and a tobacco leaf baking environment air flow velocity; storing the tobacco leaf baking environment temperature, the tobacco leaf baking environment humidity, the tobacco leaf baking environment air flow velocity, and the tobacco leaf maturity level as designated labels, and comparing the designated label with the tobacco leaf baking plans corresponding to the designated labels stored in the database to obtain the tobacco leaf baking plan corresponding to the designated label.

[0048] It needs to be explained that the above-mentioned tobacco leaf baking environment temperature refers to the ambient air temperature during the baking process. Temperature is an important factor that determines the evaporation rate of tobacco leaf moisture and the conversion of chemical composition. Infrared technology is used to measure the temperature in the drying room without contact. The tobacco leaf baking environment humidity refers to the water vapor content in the ambient air during the baking process, usually expressed as relative humidity. Humidity affects the drying speed of tobacco leaves and the final moisture content of the finished product. Capacitive humidity sensors, thin film capacitive humidity sensors, etc. can be used to monitor the relative humidity in the drying room in real time. The tobacco leaf baking environment airflow velocity refers to the speed at which the air flows in the drying room during the baking process. The airflow velocity affects the heat and moisture transfer efficiency, and thus affects the uniformity and speed of baking. It is obtained using an anemometer.

[0049] It needs to be explained that the above-mentioned temperature and humidity affect each other during the baking process. High temperature usually accelerates the evaporation of water and reduces the ambient humidity, while high humidity inhibits the rate of water evaporation, causing the temperature to rise more slowly. Temperature affects the transfer of heat, and the air flow velocity determines the distribution of heat in the drying room. A higher air flow velocity can accelerate the uniform distribution of heat and avoid local overheating or overcooling. The air flow velocity is very important for the control of humidity. A higher air flow velocity can quickly take away the evaporated water, thereby reducing the ambient humidity and promoting further drying process.

[0050] It needs to be explained that the above-mentioned most suitable baking scheme is selected according to different tobacco leaf maturity levels and environmental status parameters. Personalized optimization can ensure that each batch of tobacco leaves can reach the best state during the baking process, improve baking efficiency and quality, and unify the management of environmental status parameters and labels corresponding to maturity levels, thereby reducing quality inconsistencies caused by environmental fluctuations during the baking process, ensuring that each baking can achieve the expected effect, accurately matching environmental parameters and baking schemes, avoiding overheating, excessive dehumidification, etc., reducing energy consumption, and conducting data analysis on environmental status and baking effects, which can continuously improve baking schemes and continuously improve process levels and product quality.

[0051] The tobacco leaves are baked based on the tobacco leaf baking plan, and the tobacco leaf baking image recognition status is analyzed. Combined with the image recognition definition evaluation value, it is determined whether there is any abnormality in the tobacco leaf baking image recognition status.

[0052] The specific analysis process is as follows: obtaining a tobacco leaf baking image recognition status data set, which specifically includes the number of tobacco leaf baking breakages, the number of tobacco leaf baking deformations, and the number of abnormal tobacco leaf baking texture density; based on the obtained tobacco leaf baking image recognition status data set, a comprehensive analysis is performed to obtain an image recognition status evaluation value, which is used as an analysis basis for determining whether there is an abnormality in the tobacco leaf baking image recognition status; comparing the image recognition status evaluation value with the image recognition boundary evaluation value; if the image recognition status evaluation value is not lower than the image recognition boundary evaluation value, then there is no abnormality in the tobacco leaf baking image recognition status corresponding to the image recognition status evaluation value; if the image recognition status evaluation value is lower than the image recognition boundary evaluation value, then there is an abnormality in the tobacco leaf baking image recognition status corresponding to the image recognition status evaluation value, and an alarm is issued for tobacco leaf baking with abnormal image recognition status.

[0053] It should be explained that the number of tobacco leaves broken during baking refers to the number of cracks or fragments on the surface or inside of the tobacco leaves due to excessive drying, uneven temperature or other reasons during the baking process. The cracks or fragments will affect the physical integrity of the tobacco leaves and the quality of the final product. High-definition cameras or image acquisition equipment are used to collect high-resolution images of the tobacco leaves to capture tiny cracks or fragments. The number of tobacco leaves deformed during baking refers to the number of tobacco leaves that have changed in shape or twisted due to the uneven effects of temperature, humidity or other environmental factors during the baking process. Deformed tobacco leaves may affect the efficiency of subsequent processing and product quality. Changes in the contour of the tobacco leaves are detected by cameras and visual algorithms to determine and count the number of deformations. The number of abnormal texture density of tobacco leaves during baking refers to the number of abnormal changes in the texture structure of the tobacco leaf surface during the baking process, which may appear as a texture that is too sparse or too dense, usually due to improper baking conditions (such as excessively high temperature or inappropriate humidity). High-definition image acquisition equipment is used to collect texture images of the tobacco leaf surface, and image processing algorithms are used to analyze the texture density of the tobacco leaves to identify and count the number of abnormal areas.

[0054] It needs to be explained that the above-mentioned breakage and deformation are usually caused by similar environmental conditions, such as too high temperature or too low humidity. Too rapid drying or uneven heating can cause stress on the surface or inside of the tobacco leaves, thereby causing cracks and deformation. The breakage of tobacco leaves usually means that their physical integrity has been damaged, which may affect the texture structure on their surface. The texture density around the cracks may become abnormally sparse or dense. When the tobacco leaves are deformed, the originally evenly distributed texture may be stretched or compressed, resulting in abnormal changes in texture density.

[0055] It needs to be explained that the above-mentioned abnormalities in the image recognition status can be discovered in time during the baking process, so that measures can be taken before the problem expands to avoid damage to a large number of tobacco leaves, thereby reducing economic losses. If the abnormal tobacco leaf baking state is not corrected in time, it may affect the subsequent processing steps and cause a decline in the overall product quality. Timely alarms can avoid this situation. Through automated image recognition and anomaly detection, it can ensure that each batch of tobacco leaves meets the established quality standards, reduce the defective rate, and improve the overall product consistency and market competitiveness. The use of image recognition technology and automated alarm systems reduces dependence on manual monitoring, reduces labor costs, and improves the accuracy of monitoring.

[0056] Furthermore, the image recognition status evaluation value, the specific analysis process is:

[0057]

[0058] Where γ is the image recognition state evaluation value, sl is the number of tobacco leaf breakages, bx is the number of tobacco leaf deformations, yc is the number of abnormal texture density of tobacco leaf baking, ε1 is the compensation factor of sl, ε2 is the compensation factor of bx, ε3 is the compensation factor of yc, and e is a natural constant.

[0059] It needs to be explained that the above-mentioned image recognition status evaluation value is calculated by the number of tobacco leaves broken during baking, the number of tobacco leaves deformed during baking, and the number of abnormal texture density of tobacco leaves during baking. sl, bx, and yc are normalized. A separate evaluation of breakage, deformation, or abnormal texture density may not fully reflect the baking quality of tobacco leaves. By combining these indicators into one image recognition status evaluation value, the quality of tobacco leaves in the baking process can be more comprehensively evaluated. Integrating the evaluation values ​​of multiple indicators can reduce the judgment error caused by the fluctuation of a single indicator and improve the accuracy of the overall evaluation. Calculating and monitoring the image recognition status evaluation value can dynamically adjust the equipment operating parameters during the baking process to ensure the stability and consistency of the baking process. The long-term accumulation of image recognition status evaluation value data can be used for trend analysis and process optimization, to discover and correct potential problems in the baking process and improve production efficiency and product quality.

[0060] The tobacco leaves are cured based on the tobacco curing plan, and the chemical state of the tobacco leaves is analyzed. Combined with the chemical definition evaluation value, it is determined whether there is any abnormality in the chemical state of the tobacco leaves.

[0061] The specific analysis process is as follows: obtaining a tobacco leaf baking chemical state data set, the tobacco leaf baking chemical state data set specifically includes the absolute value of the difference between the tobacco leaf volatile organic compound content and the reference volatile organic compound content, the absolute value of the difference between the tobacco leaf nicotine and the reference nicotine, and the absolute value of the difference between the tobacco leaf pH value and the reference pH value; based on the obtained tobacco leaf baking chemical state data set, a comprehensive analysis is performed to obtain a chemical state evaluation value, and the chemical state evaluation value is used as an analysis basis for judging whether there is an abnormality in the tobacco leaf baking chemical state; comparing the chemical state evaluation value with the chemical definition evaluation value; if the chemical state evaluation value is not lower than the chemical definition evaluation value, then the tobacco leaf baking chemical state corresponding to the chemical state evaluation value does not have an abnormality; if the chemical state evaluation value is lower than the chemical definition evaluation value, then the tobacco leaf baking chemical state corresponding to the chemical state evaluation value has an abnormality, and an alarm is issued for tobacco leaf baking with an abnormal chemical state.

[0062] It should be explained that the absolute value of the difference between the above-mentioned volatile organic compound content of tobacco leaves and the volatile organic compound content of reference tobacco leaves represents the absolute value of the difference between the actual measured volatile organic compound content of tobacco leaves and the ideal or reference value. Tobacco volatile organic compounds are a class of organic compounds released by tobacco leaves during the baking process. They have an important influence on the aroma and quality of tobacco leaves. Based on the separation and quantitative analysis of various volatile organic compounds in tobacco leaves by gas chromatography (GC), the total amount or the content of specific components is determined. The absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine content The value represents the absolute value of the difference between the actual measured nicotine content and the ideal or reference value. Nicotine content is an important indicator affecting tobacco quality and smoking experience. It is based on high performance liquid chromatography (HPLC) to separate and quantitatively analyze the nicotine content in tobacco leaves and accurately determine the nicotine concentration. The absolute value of the difference between the pH value of tobacco leaves and the reference pH value represents the absolute value of the difference between the actual measured pH value of tobacco leaves and the ideal or reference pH value. The pH value reflects the acidity and alkalinity of tobacco leaves, which has an important influence on the taste and combustion characteristics of tobacco leaves. It is obtained based on a pH meter.

[0063] It needs to be explained that the above-mentioned volatile organic compounds, tobacco volatile organic compounds and nicotine are components that may undergo chemical changes during the baking process. Excessive temperature or improper humidity may accelerate the release of volatile organic compounds, and may also affect the content and structure of nicotine. When the volatile organic compound content differs greatly from the reference value, the nicotine content may also deviate greatly. The release of volatile organic compounds and changes in pH value may be affected by similar chemical environments. Excessive acidification or alkalinization conditions may change the composition of tobacco volatile organic compounds in tobacco leaves, and may also affect the stability of pH value. Abnormal volatile organic compound content may be accompanied by abnormal changes in pH value. pH value affects the release and existence form of nicotine in tobacco leaves. Higher pH value makes nicotine more easily released. Therefore, when the pH value differs greatly from the reference value, the nicotine content may also deviate from the normal range.

[0064] It needs to be explained that the above-mentioned monitoring and analysis of chemical status data can timely detect potential chemical anomalies during the tobacco leaf baking process, such as abnormal changes in volatile organic compound content, nicotine content or pH value, which helps to take corrective measures before the problem expands and prevent a large number of tobacco leaves from being damaged due to chemical anomalies. Setting chemical definition assessment values ​​and comparing them with actual chemical states can ensure the consistency of chemical composition of different batches of tobacco leaves. The alarm system can quickly notify relevant personnel when abnormal chemical states occur, and make immediate adjustments or take remedial measures, thereby reducing production delays and waste. Timely detection and correction of anomalies can avoid unnecessary resource consumption, such as excessive processing or additional remedial steps, thereby improving production efficiency and resource utilization.

[0065] Further, the chemical state evaluation value, the specific analysis process is:

[0066]

[0067] In the formula, is the chemical state assessment value, hf is the absolute value of the difference between the volatile organic compound content of tobacco leaves and the reference volatile organic compound content, ngd is the absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine, PH is the absolute value of the difference between the pH value of tobacco leaves and the reference pH value, σ1 is the compensation factor of the set hf, σ2 is the compensation factor of the set ngd, and σ3 is the compensation factor of the set PH.

[0068] It needs to be explained that the above chemical state evaluation value is calculated by the absolute value of the difference between the volatile organic compound content of tobacco leaves and the reference volatile organic compound content, the absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine, and the absolute value of the difference between the pH value of tobacco leaves and the reference pH value. HF, NGD, and PH are normalized. The chemical state evaluation value can balance the influence of each chemical indicator and avoid misleading the overall quality evaluation due to excessive fluctuation of a single indicator. By combining multiple indicators, the chemical state evaluation value can reduce the error caused by the fluctuation of a single indicator, thereby improving the accuracy of the overall evaluation. Based on the chemical state evaluation value, it can ensure that the chemical state of tobacco leaves during the baking process meets expectations, thereby optimizing the quality of the final product. As a comprehensive indicator, the chemical state evaluation value provides a standardized quality assessment tool, which can maintain consistent quality control standards in different batches of production and ensure the consistency of product quality.

[0069] Tobacco leaves are baked based on the tobacco baking plan, and the status of the tobacco baking equipment is analyzed. The evaluation value is defined in combination with the equipment status to determine whether there is any abnormality in the status of the tobacco baking equipment.

[0070] The specific analysis process is as follows: obtaining a tobacco leaf baking equipment status data set, the tobacco leaf baking equipment status data set specifically includes the number of abnormal temperature fluctuations of the tobacco leaf baking equipment, the absolute value of the difference between the actual baking time of the tobacco leaf baking equipment and the set baking time, and the smoke concentration generated by the tobacco leaf baking equipment; based on the obtained tobacco leaf baking equipment status data set, a comprehensive analysis is performed to obtain a tobacco leaf baking equipment status evaluation value, and the tobacco leaf baking equipment status evaluation value is used as an analysis basis for judging whether there is any abnormality in the tobacco leaf baking equipment status; comparing the tobacco leaf baking equipment status evaluation value with the equipment status definition evaluation value; if the tobacco leaf baking equipment status evaluation value is not lower than the equipment status definition evaluation value, then there is no abnormality in the tobacco leaf baking equipment status corresponding to the tobacco leaf baking equipment status evaluation value; if the tobacco leaf baking equipment status evaluation value is lower than the equipment status definition evaluation value, then there is an abnormality in the tobacco leaf baking equipment status corresponding to the tobacco leaf baking equipment status evaluation value, and an alarm is issued for tobacco leaf baking with abnormal equipment status.

[0071] It needs to be explained that the above-mentioned number of abnormal temperature fluctuations refers to the number of times the equipment temperature deviates from the set temperature range during the baking process. Abnormal temperature fluctuations may cause uneven baking of tobacco leaves and affect the quality of the final product. The temperature control system software analyzes temperature data, identifies and records the number of abnormal temperature fluctuations, and the absolute value of the difference between the actual baking time and the set baking time indicates the difference between the actual completed baking time and the scheduled planned time, reflecting the operating accuracy of the equipment and the control stability of the baking process. It is obtained based on the timer. The smoke concentration refers to the concentration of smoke generated during the baking process inside the equipment or in the exhaust pipe. High concentrations of smoke may indicate incomplete combustion or overheating of the material, which will affect the flavor and quality of the tobacco leaves. The smoke concentration inside the equipment or at the exhaust port is detected by smoke sensors. Commonly used ones are optical smoke sensors and ion smoke sensors.

[0072] It needs to be explained that the abnormal fluctuations in the above temperatures may cause the baking process to be extended or shortened. If the temperature fluctuates frequently, the baking may take a longer time to achieve the desired effect, resulting in an increase in the difference between the actual baking time and the set time. Frequent temperature fluctuations may lead to unstable combustion conditions, which in turn lead to incomplete combustion and increase smoke concentration. If the temperature is too high or the fluctuation is too large, it may cause local overheating, resulting in more smoke inside the tobacco leaves or baking equipment. If the actual baking time is longer than the set time (the difference is large), this may mean that the baking process is not ideal, and there may be insufficient temperature or unstable equipment operation, which may lead to incomplete combustion and produce more smoke.

[0073] It needs to be explained that when the equipment status assessment value is lower than the defined assessment value, it means that the equipment may be in an abnormal state, such as abnormal temperature fluctuations or baking time not meeting the settings. These abnormalities may directly affect the baking quality of tobacco leaves. Early warning can detect and deal with these problems in time to prevent equipment failure from causing a decline in the baking quality of tobacco leaves. Timely detection of abnormal equipment status and issuance of alarms can prevent more serious equipment failures, thereby avoiding sudden interruptions to the production line and maintaining the continuity and stability of production. Abnormal equipment status may lead to unstable baking conditions, such as excessive temperature fluctuations or inaccurate baking time. These problems will directly affect the final quality of tobacco leaves. Timely abnormal alarms can ensure precise control of baking conditions and maintain product consistency and high quality. Timely detection and correction of equipment status abnormalities can reduce defective or waste products caused by equipment problems, thereby reducing rework and scrap rates and saving production costs.

[0074] It should be explained that the above tobacco baking equipment status evaluation value is specifically analyzed as follows:

[0075]

[0076] Wherein, δ is the state evaluation value of tobacco leaf baking equipment, bd is the number of abnormal temperature fluctuations of tobacco leaf baking equipment, ht is the absolute value of the difference between the actual baking time of tobacco leaf baking equipment and the set baking time, nd is the smoke concentration generated by tobacco leaf baking equipment, τ1 is the compensation factor of the set bd, τ2 is the compensation factor of the set ht, τ3 is the compensation factor of the set nd, and e is a natural constant.

[0077] It needs to be explained that the above-mentioned tobacco baking equipment status evaluation value is calculated through the number of abnormal temperature fluctuations of the tobacco baking equipment, the absolute value of the difference between the actual baking time of the tobacco baking equipment and the set baking time, and the smoke concentration generated by the tobacco baking equipment. BD, HT, and ND are normalized, and the temperature fluctuation, baking time and smoke concentration are comprehensively considered to fully reflect the operating status of the baking equipment. Analyzing a certain indicator alone may not give a comprehensive understanding of the performance of the equipment, while the comprehensive evaluation value provides an accurate status of the overall health status of the equipment. The fluctuation of a single indicator may be due to environmental or short-term factors, but the comprehensive evaluation value can reduce false alarms caused by short-term fluctuations through the balance of multiple indicators, while improving the detection accuracy of potential equipment problems. Continuous monitoring of the equipment status evaluation value can perform predictive maintenance, take preventive measures before serious equipment failures occur, reduce sudden downtime and maintenance costs, and maintain stable equipment operation. It helps to reduce fluctuations caused by equipment problems in the production process, ensure the continuity and stability of the production process, and thus improve production efficiency.

[0078] The number of abnormal temperature fluctuations of tobacco baking equipment, the absolute value of the difference between the actual baking time of tobacco baking equipment and the set baking time, and the smoke concentration generated by tobacco baking equipment

[0079] Reference Figure 2 As shown, the second aspect of the present invention provides an abnormality monitoring system based on the tobacco leaf baking process, including a tobacco leaf maturity level comparison module, a defined evaluation value data set determination module, a tobacco leaf baking scheme determination module, an image recognition state abnormality judgment module, a chemical state abnormality judgment module and an equipment state abnormality judgment module.

[0080] The tobacco leaf maturity level comparison module is used to analyze the initial state of tobacco leaves and compare them to obtain the maturity level of tobacco leaves.

[0081] The module for determining the defined evaluation value data set is used to determine the defined evaluation value data set for tobacco leaf baking based on the maturity level of tobacco leaves. The defined evaluation value data set for tobacco leaf baking specifically includes image recognition defined evaluation value, chemical defined evaluation value and equipment status defined evaluation value.

[0082] The tobacco leaf baking plan determination module is used to analyze the tobacco leaf baking environment status and determine the tobacco leaf baking plan based on the tobacco leaf maturity level.

[0083] The image recognition state abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking plan, analyze the tobacco leaf baking image recognition state, and combine the image recognition definition evaluation value to judge whether there is an abnormality in the tobacco leaf baking image recognition state.

[0084] The chemical state abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking plan, analyze the chemical state of the tobacco leaf baking, and judge whether there is any abnormality in the chemical state of the tobacco leaf baking in combination with the chemical definition evaluation value.

[0085] The equipment status abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking plan, analyze the status of the tobacco leaf baking equipment, and determine whether there is any abnormality in the status of the tobacco leaf baking equipment in combination with the equipment status definition evaluation value.

[0086] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for monitoring abnormalities during tobacco leaf baking, characterized in that: The following steps are involved: Analyze the initial state of tobacco leaves and compare them to get the maturity level of tobacco leaves; Based on the maturity level of tobacco leaves, determining a tobacco leaf baking definition evaluation value data set, wherein the tobacco leaf baking definition evaluation value data set specifically includes an image recognition definition evaluation value, a chemical definition evaluation value, and an equipment status definition evaluation value; Analyze the tobacco leaf baking environment and determine the tobacco leaf baking plan based on the tobacco leaf maturity level; Tobacco leaves are baked based on the tobacco leaf baking scheme, and the tobacco leaf baking image recognition status is analyzed. Combined with the image recognition definition evaluation value, it is determined whether there is an abnormality in the tobacco leaf baking image recognition status; Baking tobacco leaves based on the tobacco leaf baking plan, analyzing the chemical state of tobacco leaf baking, and judging whether there is any abnormality in the chemical state of tobacco leaf baking in combination with the chemical definition evaluation value; The tobacco leaves are baked based on the tobacco baking plan, and the status of the tobacco baking equipment is analyzed. The evaluation value is defined in combination with the equipment status to determine whether there is any abnormality in the status of the tobacco baking equipment.

2. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The initial state of the tobacco leaves is analyzed and the maturity level of the tobacco leaves is obtained by comparison. The specific analysis process is as follows: Obtaining a tobacco leaf initial state data set, the tobacco leaf initial state data set specifically including the tobacco leaf initial average moisture content, the tobacco leaf initial average weight, and the tobacco leaf initial average nicotine content; Based on the acquired tobacco leaf initial state data set, the tobacco leaf initial state characteristic values ​​are obtained through comprehensive analysis, and the tobacco leaf initial state characteristic values ​​are used as the analysis basis for comparing and obtaining the tobacco leaf maturity grade; The tobacco leaf initial state characteristic value is compared with the tobacco leaf maturity level corresponding to each tobacco leaf initial state characteristic value stored in the database to obtain the tobacco leaf maturity level corresponding to the tobacco leaf initial state characteristic value.

3. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The tobacco leaf baking definition evaluation value data set is determined based on the tobacco leaf maturity level, and the specific analysis process is as follows: The tobacco leaf maturity grade is stored as a designated label, and the designated label is compared with a tobacco leaf baking definition evaluation value data set corresponding to each designated label stored in a database to obtain a tobacco leaf baking definition evaluation value data set corresponding to the designated label.

4. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The tobacco leaf baking environment state is analyzed, and the tobacco leaf baking plan is determined in combination with the tobacco leaf maturity level. The specific analysis process is as follows: Acquire a tobacco leaf baking environment state data set, the tobacco leaf baking environment state data set specifically including tobacco leaf baking environment temperature, tobacco leaf baking environment humidity, and tobacco leaf baking environment air flow velocity; The tobacco leaf baking environment temperature, tobacco leaf baking environment humidity, tobacco leaf baking environment air flow velocity and tobacco leaf maturity level are stored as designated labels, and the designated labels are compared with the tobacco leaf baking plans corresponding to the designated labels stored in the database to obtain the tobacco leaf baking plan corresponding to the designated labels.

5. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The specific analysis process of judging whether there is an abnormality in the tobacco leaf baking image recognition state is as follows: Obtain a tobacco leaf baking image recognition status dataset, wherein the tobacco leaf baking image recognition status dataset specifically includes the number of tobacco leaves that are broken during baking, the number of tobacco leaves that are deformed during baking, and the number of tobacco leaves that are abnormal in baking texture density; Based on the acquired tobacco leaf baking image recognition state data set, a comprehensive analysis is performed to obtain an image recognition state evaluation value, which is used as an analysis basis for judging whether there is an abnormality in the tobacco leaf baking image recognition state; comparing the image recognition state evaluation value with the image recognition limit evaluation value; If the image recognition state evaluation value is not lower than the image recognition boundary evaluation value, then the tobacco leaf baking image recognition state corresponding to the image recognition state evaluation value does not have any abnormality; If the image recognition state evaluation value is lower than the image recognition boundary evaluation value, then the tobacco leaf baking image recognition state corresponding to the image recognition state evaluation value is abnormal, and an alarm is issued for the tobacco leaf baking with the abnormal image recognition state.

6. The method for monitoring abnormalities during tobacco leaf baking according to claim 5, characterized in that: The image recognition state evaluation value, the specific analysis process is: Where γ is the image recognition state evaluation value, sl is the number of tobacco leaf breakages, bx is the number of tobacco leaf deformations, yc is the number of abnormal texture density of tobacco leaf baking, ε1 is the compensation factor of sl, ε2 is the compensation factor of bx, ε3 is the compensation factor of yc, and e is a natural constant.

7. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The specific analysis process of judging whether there is an abnormality in the chemical state of tobacco leaf baking is as follows: Obtain a tobacco leaf baking chemical state data set, the tobacco leaf baking chemical state data set specifically includes the absolute value of the difference between the tobacco leaf volatile organic matter content and the reference volatile organic matter content, the absolute value of the difference between the tobacco leaf nicotine and the reference nicotine, and the absolute value of the difference between the tobacco leaf pH value and the reference pH value; Based on the acquired tobacco leaf baking chemical state data set, a chemical state evaluation value is obtained through comprehensive analysis, and the chemical state evaluation value is used as an analytical basis for judging whether there is an abnormality in the tobacco leaf baking chemical state; Comparing the chemical status assessment with the chemical qualification assessment; If the chemical status assessment value is not lower than the chemical definition assessment value, then the tobacco leaf baking chemical state corresponding to the chemical status assessment value does not have abnormality; If the chemical state evaluation value is lower than the chemical definition evaluation value, then the tobacco leaf baking chemical state corresponding to the chemical state evaluation value is abnormal, and an alarm is issued for the tobacco leaf baking with abnormal chemical state.

8. The method for monitoring abnormalities during tobacco leaf baking according to claim 7, characterized in that: The chemical state evaluation value, the specific analysis process is: In the formula, is the chemical state assessment value, hf is the absolute value of the difference between the volatile organic compound content of tobacco leaves and the reference volatile organic compound content, ngd is the absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine, PH is the absolute value of the difference between the pH value of tobacco leaves and the reference pH value, σ1 is the compensation factor of the set hf, σ2 is the compensation factor of the set ngd, and σ3 is the compensation factor of the set PH.

9. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, characterized in that: The specific analysis process of judging whether the tobacco leaf baking equipment state is abnormal is as follows: Obtain a tobacco leaf baking equipment status data set, which specifically includes the number of abnormal temperature fluctuations of the tobacco leaf baking equipment, the absolute value of the difference between the actual baking time of the tobacco leaf baking equipment and the set baking time, and the smoke concentration generated by the tobacco leaf baking equipment; Based on the acquired tobacco leaf baking equipment status data set, a tobacco leaf baking equipment status evaluation value is obtained through comprehensive analysis, and the tobacco leaf baking equipment status evaluation value is used as an analysis basis for judging whether there is an abnormality in the tobacco leaf baking equipment status; Compare the tobacco leaf curing equipment condition assessment value with the equipment condition definition assessment value; If the tobacco leaf baking equipment state evaluation value is not lower than the equipment state definition evaluation value, then there is no abnormality in the tobacco leaf baking equipment state corresponding to the tobacco leaf baking equipment state evaluation value; If the tobacco leaf baking equipment state evaluation value is lower than the equipment state definition evaluation value, then the tobacco leaf baking equipment state corresponding to the tobacco leaf baking equipment state evaluation value is abnormal, and an alarm is issued for the tobacco leaf baking equipment state with abnormality.

10. A system for monitoring abnormalities during tobacco leaf baking, applied to a method for monitoring abnormalities during tobacco leaf baking as claimed in any one of claims 1 to 9, characterized in that: It includes a tobacco leaf maturity level comparison module, a defined evaluation value data set determination module, a tobacco leaf baking plan determination module, an image recognition state abnormality judgment module, a chemical state abnormality judgment module and an equipment state abnormality judgment module, among which: The tobacco leaf maturity level comparison module is used to analyze the initial state of the tobacco leaves and obtain the tobacco leaf maturity level by comparison; The defined evaluation value data set determination module is used to determine the tobacco leaf baking defined evaluation value data set based on the tobacco leaf maturity level, and the tobacco leaf baking defined evaluation value data set specifically includes the image recognition defined evaluation value, the chemical defined evaluation value and the equipment status defined evaluation value; The tobacco leaf baking scheme determination module is used to analyze the tobacco leaf baking environment state and determine the tobacco leaf baking scheme in combination with the tobacco leaf maturity level; The image recognition state abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking scheme, analyze the tobacco leaf baking image recognition state, and judge whether there is an abnormality in the tobacco leaf baking image recognition state in combination with the image recognition definition evaluation value; The chemical state abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking scheme, analyze the chemical state of the tobacco leaf baking, and judge whether there is an abnormality in the chemical state of the tobacco leaf baking in combination with the chemical definition evaluation value; The equipment status abnormality judgment module is used to bake tobacco leaves based on the tobacco leaf baking plan, analyze the status of the tobacco leaf baking equipment, and determine whether there is an abnormality in the status of the tobacco leaf baking equipment in combination with the equipment status definition evaluation value.

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