Abnormality monitoring method and system based on tobacco leaf baking process

Abstract

The present invention relates to the technical field of tobacco leaf baking data recognition, and specifically discloses a method and system for monitoring anomalies in a tobacco leaf baking process, the method comprising: analyzing the initial state of the tobacco leaves, obtaining the maturity level of the tobacco leaves by comparison and determining a tobacco leaf baking definition evaluation value data set, analyzing the tobacco leaf baking environment state, determining the tobacco leaf baking plan, and judging whether there are anomalies in the tobacco leaf baking image recognition state, chemical state, and equipment state. The present invention solves the problems of low accuracy, insufficient automation, and large fluctuations in tobacco leaf quality in traditional tobacco leaf baking anomaly monitoring methods, and can ensure that each batch of tobacco leaves is processed under optimal conditions. Unified processing standards and monitoring systems help maintain quality consistency in the production process, avoid over- or under-baking, monitor the image, chemical, and equipment states during the baking process, quickly identify deviations and make adjustments to avoid the expansion of quality problems.

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. The development of an effective abnormality monitoring system is 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, avoid raw material loss, and thus improve overall production efficiency. With the development of sensing technology, data analysis and artificial intelligence, the automation and intelligence of the tobacco leaf baking process have become possible. Using these advanced technologies for abnormality monitoring can not only improve the accuracy and response speed of monitoring, but also achieve more advanced predictive maintenance and optimized decision-making.

[0003] At present, there are still some deficiencies 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 inability to ensure the quality consistency of each batch of tobacco leaves. The low-precision monitoring method may lead to the inability to detect abnormalities in production in a timely manner, such as improper temperature and humidity control, which may cause 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: The first aspect of the present invention provides a method for monitoring abnormalities in the tobacco leaf baking process, comprising the following steps: analyzing the initial state of the tobacco leaves and obtaining the tobacco leaf maturity level by comparison; determining a tobacco leaf baking definition evaluation value data set based on the tobacco leaf maturity level, the tobacco leaf baking definition evaluation value data set specifically including 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 tobacco leaf maturity level; baking the tobacco leaves based on the tobacco leaf baking scheme, analyzing the tobacco leaf baking image recognition state, and judging whether the tobacco leaf baking image recognition state is abnormal 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 the tobacco leaf baking chemical state is abnormal 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 the tobacco leaf baking equipment state is abnormal in combination with the equipment state definition evaluation value.

[0006] As a further method, 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: obtaining a tobacco leaf initial state data set, which specifically includes the initial average moisture content of the tobacco leaves, the initial average weight of the tobacco leaves, and the initial average nicotine content of the tobacco leaves; based on the obtained tobacco leaf initial state data set, a comprehensive analysis is performed to obtain the tobacco leaf initial state characteristic value, and the tobacco leaf initial state characteristic value is used as the analysis basis for obtaining the tobacco leaf maturity level by comparison; 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.

[0007] As a further method, a tobacco leaf curing definition evaluation value dataset is determined based on the tobacco leaf maturity grade. The specific analysis process is: the tobacco leaf maturity grade is stored as a designated label, and the designated label is compared with the tobacco leaf curing definition evaluation value dataset corresponding to each designated label stored in the database to obtain the tobacco leaf curing definition evaluation value dataset corresponding to the designated 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 the 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. The specific analysis process is: obtaining 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 obtained 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 determining whether there is an abnormality in the tobacco leaf baking image recognition state; comparing the image recognition state evaluation value 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 the tobacco leaf baking image recognition state corresponding to the image recognition state evaluation value does not have an 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 has an abnormality, and an alarm is issued for tobacco leaf baking with an abnormal image recognition state.

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

[0011]

[0012] Where γ is the image recognition state evaluation value, sl is the number of tobacco leaves broken during baking, bx is the number of tobacco leaves deformed during baking, yc is the number of abnormal texture density of tobacco leaves, ε1 is the compensation factor of the set sl, ε2 is the compensation factor of the set bx, ε3 is the compensation factor of the set 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. The specific analysis process is: obtain a tobacco leaf baking chemical state data set, which 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, which is used as an analysis basis for determining whether there is any abnormality in the tobacco leaf baking chemical state; compare 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 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 an abnormal chemical state.

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

[0015]

[0016] Where, 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 content, 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 for the set hf, σ2 is the compensation factor for the set ngd, and σ3 is the compensation factor for the set pH.

[0017] As a further method, it is determined whether there is an abnormality in the state of the tobacco baking equipment. The specific analysis process is: obtaining a tobacco baking equipment state data set, the tobacco baking equipment state data set specifically includes 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; based on the obtained tobacco baking equipment state data set, a comprehensive analysis is performed to obtain a tobacco baking equipment state evaluation value, and the tobacco baking equipment state evaluation value is used as an analysis basis for determining whether there is an abnormality in the state of the tobacco baking equipment; the tobacco baking equipment state evaluation value is compared with the equipment state definition evaluation value; if the tobacco baking equipment state evaluation value is not lower than the equipment state definition evaluation value, then there is no abnormality in the tobacco baking equipment state corresponding to the tobacco baking equipment state evaluation value; if the tobacco baking equipment state evaluation value is lower than the equipment state definition evaluation value, then there is an abnormality in the tobacco baking equipment state corresponding to the tobacco 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 obtain the tobacco leaf maturity level by comparison; 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 tobacco leaf baking equipment state, 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. By accurately setting baking parameters based on maturity levels, each batch of tobacco leaves can be 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 accurately controlling baking parameters, over- or under-baking can be avoided, thereby reducing the waste of raw materials and energy. By monitoring the image, chemical 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), and reducing raw material waste 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, thereby ensuring 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 tobacco leaf loss caused by improper baking, such as carbonization of tobacco leaves caused by over-baking or insufficient baking affecting the quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described with reference to the accompanying drawings. However, 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 effort.

[0024] Figure 1 Schematic diagram of the method steps of the present invention.

[0025] Figure 2 This is a schematic diagram of system module connections 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 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 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 the tobacco leaf initial state characteristic value, which is used as the analysis basis for comparing and obtaining the tobacco leaf maturity grade; comparing the tobacco leaf initial state characteristic value with the tobacco leaf maturity grade corresponding to each tobacco leaf initial state characteristic value stored in the database to obtain the tobacco leaf maturity grade corresponding to the tobacco leaf initial state characteristic value.

[0031] In a specific embodiment, the specific analysis process of the tobacco leaf initial state characteristic value is as follows:

[0032]

[0033] Where 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 evaluated more comprehensively. 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 judged more accurately. According to the initial state characteristic values ​​of tobacco leaves, 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, the characteristic value of the initial state of tobacco leaves changes 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, this 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 average nicotine content of tobacco leaves, and the y-axis represents the initial state characteristic value of tobacco leaves. It can help us intuitively understand how the initial average nicotine content of tobacco leaves affects the initial state characteristic value of tobacco leaves. The larger the initial average 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 average 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 size of the initial average nicotine content of tobacco leaves is changed. 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 (grams) 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, and ng set above are obtained from the database. Based on 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, and ng is established to obtain the compensation factors of hs, zl, and ng corresponding to the current hs, zl, and 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 the database, that is, the corresponding compensation factors are obtained based on the current data.

[0040] It should 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, which is 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, resulting in a relative decrease in the nicotine content (concentration) per unit mass. 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 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 judgment based on experience or appearance alone, and improve the scientificity and consistency of judgment. Comparing the characteristic values ​​of the initial state of tobacco leaves with the characteristic values ​​of known maturity levels in the database can detect abnormal conditions in the maturation process of tobacco leaves 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, the tobacco leaf baking definition evaluation value data set is determined. The tobacco leaf baking definition evaluation value data set specifically includes image recognition definition evaluation value, chemical definition evaluation value and equipment status definition evaluation value.

[0044] The specific analysis process is: store the tobacco leaf maturity level as a designated label, compare the designated label with the tobacco leaf baking definition evaluation value data set corresponding to each designated label stored in the database, and obtain 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 baking parameter matching 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: obtain the tobacco leaf baking environment status data set, which specifically includes the tobacco leaf baking environment temperature, tobacco leaf baking environment humidity, and tobacco leaf baking environment air flow velocity; store the tobacco leaf baking environment temperature, tobacco leaf baking environment humidity, tobacco leaf baking environment air flow velocity and tobacco leaf maturity level as designated labels, and compare the designated label 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.

[0048] It should 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 capacitor 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 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, and 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 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 should be explained that the above-mentioned selection of the most appropriate baking scheme 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 the occurrence of overheating, excessive dehumidification, etc., reducing energy consumption, and conducting data analysis of 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 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 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 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 judging whether there is an abnormality in the tobacco leaf baking image recognition status; comparing the image recognition status evaluation value with the image recognition delimitation evaluation value; if the image recognition status evaluation value is not lower than the image recognition delimitation evaluation value, then the tobacco leaf baking image recognition status corresponding to the image recognition status evaluation value does not have an abnormality; if the image recognition status evaluation value is lower than the image recognition delimitation evaluation value, then the tobacco leaf baking image recognition status corresponding to the image recognition status evaluation value is abnormal, and an alarm is issued for tobacco leaf baking with abnormal image recognition status.

[0053] It should be explained that the above-mentioned 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. 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 too 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, which 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 destroyed, which may affect the texture structure of 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 are 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 status 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 be ensured 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 as follows:

[0057]

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

[0059] It should 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 tobacco leaves with abnormal texture density during baking. sl, bx, and yc are normalized. The evaluation of breakage, deformation, or texture density abnormality alone 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 fluctuations in 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, which 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, which is used as an analysis basis for judging whether there is any 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 is not abnormal; 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 tobacco leaf baking with abnormal chemical state.

[0062] It should be explained that the absolute value of the difference between the 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 content of specific components is determined. The absolute value of the difference between the nicotine content of tobacco leaves and the reference nicotine content is 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. Based on high-performance liquid chromatography (HPLC), the nicotine content in tobacco leaves is separated and quantitatively analyzed to accurately determine the nicotine concentration. The absolute value of the difference between the tobacco leaf pH value and the reference pH value represents the absolute value of the difference between the actual measured tobacco leaf pH value and the ideal or reference pH value. The pH value reflects the acidity and alkalinity of the tobacco leaf and has a significant impact on the taste and burning characteristics of the tobacco leaf. 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 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 large quantities 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 chemical status anomalies occur, and immediately make adjustments or take remedial measures, thereby reducing production delays and waste. Timely detection and correction of anomalies can avoid unnecessary resource consumption, such as over-processing or additional remedial steps, thereby improving production efficiency and resource utilization.

[0065] Furthermore, the chemical state evaluation value, the specific analysis process is as follows:

[0066]

[0067] Where, 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 content, 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 for the set hf, σ2 is the compensation factor for the set ngd, and σ3 is the compensation factor for the set pH.

[0068] It should be explained that the above-mentioned 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 the excessive fluctuation of a single indicator to mislead the overall quality assessment. 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 assessment. 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 consistency in product quality.

[0069] Tobacco leaves are cured based on the tobacco curing plan, and the status of the tobacco curing 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 curing equipment.

[0070] The specific analysis process is as follows: obtaining 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 obtained tobacco leaf baking equipment status data set, a comprehensive analysis is performed to obtain a tobacco leaf baking equipment status evaluation value, which 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 should 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 baking time and the 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, baking may take longer 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 leads to incomplete combustion and increased 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 thus 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 timely detect and deal with these problems to prevent equipment failures from causing a decline in tobacco leaf baking quality. 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 production continuity and stability. 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. Through timely abnormal alarms, precise control of baking conditions can be ensured to 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 specific analysis process of the above tobacco leaf curing equipment status evaluation value is as follows:

[0075]

[0076] Where δ is the state evaluation value of the tobacco leaf curing equipment, bd is the number of abnormal temperature fluctuations of the tobacco leaf curing equipment, ht is the absolute value of the difference between the actual curing time of the tobacco leaf curing equipment and the set curing time, nd is the smoke concentration generated by the tobacco leaf curing 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 should 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 comprehensive consideration is given to temperature fluctuations, baking time, and smoke concentration, which can 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. Fluctuations in 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 shutdowns and maintenance costs, and maintain stable equipment operation. This helps reduce fluctuations caused by equipment problems during 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 leaf baking equipment, the absolute value of the difference between the actual baking time of tobacco leaf baking equipment and the set baking time, and the concentration of smoke generated by tobacco leaf 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 obtain the maturity level of tobacco leaves by comparison.

[0081] 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. The tobacco leaf baking defined evaluation value data set specifically includes image recognition defined evaluation value, chemical defined evaluation value and equipment status defined evaluation value.

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

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

[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 leaves during baking, and judge whether there is any abnormality in the chemical state of the tobacco leaves during 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 content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments 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 scope of protection 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 obtain the maturity level of tobacco leaves; Determine a tobacco leaf curing definition evaluation value data set based on the tobacco leaf maturity level, wherein the tobacco leaf curing 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 curing environment and determine the tobacco leaf curing plan based on the tobacco leaf maturity level; Tobacco leaves are baked based on the tobacco baking plan, and the tobacco 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 baking image recognition status; 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; Tobacco leaves are cured based on the tobacco curing plan, and the status of tobacco curing equipment is analyzed. Based on the equipment status, an assessment value is defined to determine whether there are any abnormalities in the tobacco curing equipment status. The specific analysis process for determining 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, which 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 with abnormal baking texture density; Based on the acquired tobacco leaf baking image recognition status dataset, 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 any abnormality in the tobacco leaf baking image recognition status. comparing the image recognition state evaluation value 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 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 abnormal image recognition state; The specific analysis process of the image recognition status evaluation value is as follows: ； Where, is the image recognition status evaluation value, The number of broken tobacco leaves after baking. The number of tobacco leaves deformed during baking. The number of abnormal density of tobacco leaf baking textures, For the setting The compensation factor, For the setting The compensation factor, For the setting The compensation factor, e is a natural constant; The specific analysis process for judging whether there is an abnormality in the chemical state of tobacco leaf baking is as follows: Obtain a tobacco leaf curing chemical state data set, the tobacco leaf curing chemical state data set specifically including 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 content and the reference nicotine content, and the absolute value of the difference between the tobacco leaf pH value and the reference pH value; Based on the acquired tobacco leaf curing chemical state data set, a comprehensive analysis is performed to obtain a chemical state evaluation value, which is used as an analytical basis for determining whether there is an abnormality in the tobacco leaf curing chemical state. Comparing chemical status assessments with chemical qualification assessments; 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 abnormalities; If the chemical state evaluation value is lower than the chemical definition evaluation value, the chemical state of the tobacco leaves corresponding to the chemical state evaluation value is abnormal, and an alarm is issued for the tobacco leaves with abnormal chemical state; The specific analysis process of the chemical state evaluation value is as follows: ； Where, is the chemical status assessment value, is the absolute value of the difference between the volatile organic compound content of tobacco leaves and the reference volatile organic compound content, is the absolute value of the difference between tobacco leaf nicotine and reference nicotine, is the absolute value of the difference between the pH value of tobacco leaves and the reference pH value, For the setting The compensation factor, For the setting The compensation factor, For the setting The compensation factor; The specific analysis process for judging whether the tobacco leaf baking equipment is abnormal is as follows: Obtain a tobacco leaf curing equipment status data set, which specifically includes the number of abnormal temperature fluctuations of the tobacco leaf curing equipment, the absolute value of the difference between the actual curing time of the tobacco leaf curing equipment and the set curing time, and the smoke concentration generated by the tobacco leaf curing equipment; Based on the acquired tobacco leaf curing equipment status data set, a comprehensive analysis is performed to obtain a tobacco leaf curing equipment status evaluation value, which is used as an analysis basis for determining whether the tobacco leaf curing equipment status is abnormal. Compare the tobacco leaf curing equipment condition assessment value with the equipment condition definition assessment value; If the tobacco leaf curing equipment state evaluation value is not lower than the equipment state definition evaluation value, then the tobacco leaf curing equipment state corresponding to the tobacco leaf curing equipment state evaluation value does not have an abnormality; 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.

2. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, wherein: The initial state of the tobacco leaves is analyzed and compared to obtain the maturity level of the tobacco leaves. 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 obtained tobacco leaf initial state data set, a comprehensive analysis is performed to obtain the tobacco leaf initial state characteristic values, which 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, wherein: The tobacco leaf baking definition evaluation value dataset is determined based on the tobacco leaf maturity level. 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 the tobacco leaf curing definition evaluation value data set corresponding to each designated label stored in the database to obtain the tobacco leaf curing definition evaluation value data set corresponding to the designated label.

4. The method for monitoring abnormalities during tobacco leaf baking according to claim 1, wherein: The tobacco leaf curing environment state is analyzed and the tobacco leaf curing plan is determined in combination with the tobacco leaf maturity level. The specific analysis process is as follows: Obtain a tobacco leaf curing environment state data set, the tobacco leaf curing environment state data set specifically including tobacco leaf curing environment temperature, tobacco leaf curing environment humidity, and tobacco leaf curing environment airflow 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. 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 4, characterized in that: It includes a tobacco leaf maturity grade 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 delimiting evaluation value data set determination module is used to determine a tobacco leaf curing delimiting evaluation value data set based on the tobacco leaf maturity level, wherein the tobacco leaf curing delimiting evaluation value data set specifically includes an image recognition delimiting evaluation value, a chemical delimiting evaluation value, and an equipment status delimiting evaluation value; The tobacco leaf curing scheme determination module is used to analyze the tobacco leaf curing environment state and determine the tobacco leaf curing scheme in combination with the tobacco leaf maturity level; The image recognition state abnormality judgment module is used to perform baking on tobacco leaves based on the tobacco leaf baking plan, analyze the tobacco leaf baking image recognition state, and determine 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 perform chemical analysis on the tobacco leaves during baking based on the tobacco leaf baking scheme, and determine whether there is an abnormality in the chemical state of the tobacco leaves during 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 tobacco leaf baking equipment status in combination with the equipment status definition evaluation value.

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