Method and system for controlling tobacco leaf baking temperature and humidity in rainy weather

Abstract

The invention relates to the technical field of tobacco leaf curing modulation, and discloses a rainy weather tobacco leaf curing temperature and humidity control method and system.The rainy weather tobacco leaf curing temperature and humidity control method comprises the following steps that temperature and humidity data of multiple positions in a tobacco loading chamber of a bulk curing barn are collected and analyzed in real time based on a temperature and humidity sensor; the influence of rainy weather on humiture fluctuation in a tobacco loading chamber of the bulk curing barn is evaluated, the change trend of humiture is identified, and humiture monitoring data is generated; by collecting and analyzing temperature and humidity data of multiple positions in the tobacco loading chamber of the bulk curing barn in real time, the actual influence of air temperature and humidity in rainy weather on the curing environment is evaluated, power input and response of curing heat supply equipment are analyzed and adjusted, the stability and reliability of the curing process under the severe weather condition are ensured, and the curing efficiency is improved. The infrared spectrum sensor is used for monitoring changes of various compounds in the tobacco leaf curing process in real time, curing parameters are adjusted, and the tobacco leaf bulk curing quality is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of tobacco leaf baking and modulation, and in particular relates to a method and system for controlling temperature and humidity of tobacco leaf baking in rainy weather. Background Art

[0002] Tobacco leaf baking is an important link in tobacco leaf production. In intensive baking rooms, the quality of the final tobacco leaf product can be controlled by controlling parameters such as temperature, humidity, time and wind speed during the baking process. However, tobacco leaf baking is currently affected by environmental and human factors, and the baking loss rate is relatively high, which affects the quality of tobacco leaves. A variety of modern machinery and automation technologies are used to achieve standardization and mass production of tobacco leaf baking, reduce human error operations and production costs, and achieve automation and intelligence of tobacco leaf baking by scientifically controlling baking temperature and humidity parameters, thereby improving the homogenization of intensively baked tobacco leaves and improving the appearance, internal and sensory quality of tobacco leaves.

[0003] Tobacco-growing areas in southern my country experience more rainfall during the tobacco-curing season, which affects the tobacco-curing characteristics, increases the risk of tobacco being damaged, and reduces the quality of the tobacco-curing. A method for controlling temperature and humidity in tobacco-curing in rainy weather aims to achieve continuous rainy weather when tobacco is cured, thereby controlling the temperature and humidity of the curing environment to ensure that the tobacco-curing process is not affected by external humidity, and to prevent the tobacco-curing quality from being reduced due to the inhalation of a large amount of cold and humid air during the curing process, including curing green leaves in high-temperature areas and rotting of dregs in low-temperature areas. Combined with an automated control system and temperature and humidity sensors, the curing environment is monitored and adjusted in real time, and the temperature and humidity conditions in the curing room are maintained, thereby ensuring that an ideal curing effect is achieved under adverse weather conditions, maintaining the curing quality and intrinsic quality of tobacco leaves such as color, structure, oil content, and integrity during the curing process, and meeting the production needs of high-quality tobacco leaves.

[0004] In actual operation, traditional tobacco leaf baking temperature and humidity control methods cannot accurately adjust baking parameters in real time and match rapidly changing temperature and humidity conditions, resulting in difficulty in maintaining ideal climate conditions in the tobacco loading room during continuous rainy days, causing a decline in tobacco leaf baking quality, including green baking, ash hanging, stiffness, etc. There are delays in data integration and real-time feedback, which affects the optimization of baking efficiency and energy consumption, limits the controllability and predictability of the baking process, increases baking costs and labor intensity, and reduces the commercial quality of tobacco leaves. Summary of the invention

[0005] The main technical problem to be solved by the present invention is to provide a method and system for controlling temperature and humidity of tobacco leaf baking in rainy weather, which can ensure the stability and reliability of the baking process under adverse weather conditions, improve the homogenization, automation and intelligence of intensive baking of tobacco leaves, reduce human errors and production costs, and thus improve the appearance, internal and sensory quality of tobacco leaves, and improve the availability of industrial baking of tobacco leaves.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: A method for controlling temperature and humidity of tobacco leaf baking in rainy weather, comprising the following steps: Based on the temperature and humidity sensors, the temperature and humidity data of multiple locations in the smoke-loading room of the intensive curing barn are collected and analyzed in real time, the impact of rainy weather on the temperature and humidity fluctuations in the smoke-loading room of the intensive curing barn is evaluated, and the trend of temperature and humidity changes is identified to generate temperature and humidity monitoring data; Based on the temperature and humidity monitoring data, analyze the mutual influence and dependence between temperature and humidity, and generate interaction analysis results; Using the interaction analysis results, evaluate the relationship between the power input and temperature and humidity changes of the baking equipment, analyze the temperature and humidity adjustment efficiency of multiple baking equipment, and form adjustment efficiency evaluation data; Based on the regulation efficiency evaluation data, infrared spectroscopy sensors are used to analyze the infrared response characteristics of various tobacco leaf compounds online. By real-time monitoring of tobacco leaves, changes in the content of various compounds are identified and chemical composition monitoring records are generated. Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time. The tobacco leaf quality requirements at multiple baking stages are considered, the ambient temperature and humidity that need to be adjusted are analyzed, and the temperature and humidity adjustment requirements information is formulated; Based on the temperature and humidity adjustment demand information, combined with the mutual influence between temperature and humidity, and considering the rainy environmental conditions, the control parameters of the baking equipment are monitored and adjusted in real time to generate baking temperature and humidity control records.

[0007] Further optimization: the temperature and humidity monitoring data include temperature change amplitude information, humidity change amplitude information, and temperature and humidity change trend chart; the interaction analysis results include the sensitivity index of temperature on humidity regulation, the response time of humidity on temperature, and the interdependence coefficient of temperature and humidity regulation; the regulation efficiency evaluation data include baking equipment energy efficiency grade, power regulation response speed, and temperature and humidity control energy consumption ratio information; the chemical composition monitoring records include characteristic compound infrared absorption peak, compound content change trend, and chemical reaction rate analysis results; the temperature and humidity adjustment demand information includes temperature demand analysis results, humidity control level indicators, and baking stage information; the baking temperature and humidity control records include real-time data of temperature and humidity in the smoke loading room of the intensive baking room, temperature and humidity matching data, and equipment adjustment parameter configuration.

[0008] Further optimization: Based on the temperature and humidity sensors, real-time collection and analysis of temperature and humidity data at multiple locations in the dense smoke-curing room, evaluation of the impact of rainy weather on the temperature and humidity fluctuations in the dense smoke-curing room, and identification of the changing trend of temperature and humidity. The specific steps for generating temperature and humidity monitoring data are as follows: Based on temperature and humidity sensors, considering coverage and monitoring efficiency, temperature and humidity sensors are deployed at multiple locations in the smoke loading room of the dense curing room to collect temperature and humidity data in real time, obtain real-time temperature and humidity data, and establish a deployment record of temperature and humidity sensors; Based on the deployment records of temperature and humidity sensors, the data fluctuations at multiple time points and locations are compared to analyze and identify the impact of rainy weather on data fluctuations, and generate temperature and humidity fluctuation information; Based on the temperature and humidity fluctuation information, evaluate and predict the changing trend of temperature and humidity data, identify the temperature and humidity change patterns in rainy weather, and generate temperature and humidity monitoring data.

[0009] Further optimization: Based on the temperature and humidity monitoring data, the mutual influence and dependence between temperature and humidity are analyzed. The specific steps for generating the interaction analysis results are as follows: Based on the temperature and humidity monitoring data, analyze the impact of ambient temperature changes on humidity, record the humidity adjustment requirements caused by temperature changes, and generate impact relationship analysis data; Based on the impact relationship analysis data, evaluate the impact of humidity changes on temperature, record the temperature adjustment requirements caused by humidity changes, and generate humidity impact assessment information; Based on the humidity impact assessment information, the mutual influence relationship and dependency between temperature and humidity are evaluated, and the interaction analysis results are generated.

[0010] Further optimization: Using the interaction analysis results, evaluate the relationship between the power input and temperature and humidity changes of the baking equipment, analyze the temperature and humidity adjustment efficiency of multiple baking equipment, and form the adjustment efficiency evaluation data in the following steps: Based on the interaction analysis results, the response time and adjustment range of multiple baking equipment under different environmental conditions are analyzed to generate equipment response characteristic data; Based on the equipment response characteristic data, the power consumption and temperature and humidity adjustment efficiency of multiple baking equipment under differentiated temperature and humidity changes are calculated to generate equipment efficiency data; Based on the equipment efficiency data, considering the mutual influence and dependency between temperature and humidity, the parameter configuration of various temperature and humidity adjustment requirements is calculated to generate adjustment efficiency evaluation data.

[0011] Further optimization: Based on the regulation efficiency evaluation data, infrared response characteristics of various tobacco leaf compounds are analyzed online using infrared spectroscopy sensors. By real-time monitoring of tobacco leaves, changes in the content of various compounds are identified. The steps for generating chemical composition monitoring records are as follows: Based on the regulation efficiency evaluation data, the spectral responses of various tobacco leaf compounds are collected and analyzed using an infrared spectral sensor, the spectral data are recorded, and tobacco leaf spectral recording data is generated; Based on the tobacco leaf spectrum recording data, the infrared response characteristics of multiple key compounds in tobacco leaves, including nicotine and sugars, are identified, the content changes of multiple compounds during the baking process are monitored, and compound content change data are generated; The compound content change data is used in combination with real-time temperature and humidity data to evaluate the changing trends of the contents of multiple compounds and generate chemical composition monitoring records.

[0012] Further optimization: Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time. The tobacco leaf quality requirements at multiple baking stages are considered, and the ambient temperature and humidity that need to be adjusted are analyzed. The specific steps for formulating the temperature and humidity adjustment requirements information are as follows: Based on the chemical composition monitoring records, the content data of multiple key compounds are analyzed and compared with the quality standards to predict and evaluate the quality of tobacco leaves during the baking process and generate quality level analysis results; Based on the quality level analysis results, by analyzing the tobacco leaf quality requirements in multiple baking stages, the deviation between the baking environment and the ideal quality target is evaluated in real time, and the adjustment target identification results are generated; According to the adjustment target identification results, the changing trends of tobacco leaf compounds under various temperature and humidity conditions are considered, the temperature and humidity parameters that need to be adjusted are identified, and the temperature and humidity adjustment demand information is generated.

[0013] Further optimization: Based on the temperature and humidity adjustment demand information, combined with the mutual influence between temperature and humidity, and considering the rainy environment conditions, the control parameters of the baking equipment are monitored and adjusted in real time. The specific steps for generating the baking temperature and humidity control record are as follows: Based on the temperature and humidity adjustment demand information, real-time monitoring of temperature and humidity data in multiple areas of the smoke-loading room in a densely populated curing room under rainy conditions is performed to adjust control parameters to match baking requirements and generate control parameter adjustment records; Based on the control parameter adjustment records, the fuzzy logic control method is used to consider the mutual influence between temperature and humidity and the temperature and humidity adjustment efficiency of the baking equipment, adjust the temperature and humidity control parameters of the baking equipment, and generate the adjustment parameter optimization record; Based on the adjustment parameter optimization record, apply the temperature and humidity adjustment parameters, monitor the temperature and humidity adjustment effect in real time, evaluate the consistency with the baking requirements, and generate the baking temperature and humidity control record.

[0014] Further optimization: The fuzzy logic control method, according to the formula: ; Calculate the adjustment value of the temperature and humidity control parameters, where: is the adjustment value of the control parameter, is the error between target and actual temperature and humidity, is the time variable, is the proportional gain, is the integral gain, is the differential gain, is the environmental change rate, is a stability indicator, is the weight coefficient of the environmental change rate, is the weight coefficient of the stability index, Indication error About time The differential of Indication error About time The integral of is the differential symbol, is the time differential, Error The differential of .

[0015] The present invention also provides a rainy weather tobacco leaf baking temperature and humidity control system, which is used to execute the rainy weather tobacco leaf baking temperature and humidity control method, and the system comprises: The environmental data acquisition module is based on temperature and humidity sensors, which monitor the temperature and humidity data of multiple locations in the dense smoke-curing room in real time, evaluate the impact of rainy weather on the temperature and humidity fluctuations in the dense smoke-curing room, and generate a temperature and humidity data set; The influence relationship analysis module calculates the interaction strength between temperature and humidity based on the temperature and humidity data set, evaluates the impact of ambient temperature changes on humidity, and generates dependency evaluation results; The regulation capability analysis module analyzes the relationship between the power input and temperature and humidity changes of the baking equipment based on the dependency evaluation results, evaluates the temperature and humidity regulation efficiency of multiple baking equipment, and generates equipment efficiency evaluation information; The real-time quality monitoring module uses infrared spectroscopy sensors to monitor the infrared response of tobacco leaf compounds in the baking process in real time based on equipment efficiency evaluation information, analyzes changes in compound content, predicts tobacco leaf quality during the baking process, and generates tobacco leaf quality prediction results; The parameter adjustment control module is based on the tobacco leaf quality prediction results, considers the mutual influence between temperature and humidity, monitors and adjusts the control parameters of the baking equipment in real time to match the rainy environment, and generates baking temperature and humidity control records.

[0016] The present invention adopts the above technical solution and has the following beneficial effects: The present invention collects and analyzes temperature and humidity data at multiple locations in the tobacco-loading room of an intensive curing barn in real time, evaluates the actual impact of air temperature and humidity on the baking environment in rainy weather, evaluates the interaction between temperature and humidity, analyzes and adjusts the power input and response of the baking equipment, ensures the stability and reliability of the baking process under adverse weather conditions, uses infrared spectroscopy sensors to monitor the content changes of various compounds in the tobacco leaf baking process in real time and adjusts the baking parameters, improves the homogenization, automation and intelligence of the intensive baking of tobacco leaves, reduces human errors and production costs, thereby improving the appearance, internal and sensory quality of tobacco leaves, and improving the availability of industrial baking of tobacco leaves; and can also improve the storage stability, combustion performance and taste of tobacco leaves, meeting the production needs of high-quality tobacco leaves.

[0017] The present invention is further described below in conjunction with the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the working process of an embodiment of the present invention; Figure 2 is a detailed flow chart of step S1 in an embodiment of the present invention; Figure 3 is a detailed flow chart of step S2 in an embodiment of the present invention; Figure 4 is a detailed flow chart of step S3 in an embodiment of the present invention; Figure 5 is a detailed flow chart of step S4 in an embodiment of the present invention; Figure 6 is a detailed flow chart of step S5 in an embodiment of the present invention; Figure 7 is a detailed flow chart of step S6 in an embodiment of the present invention; Figure 8 4 is a flow chart of a control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] See also Figure 1 , a method for controlling temperature and humidity of tobacco leaf baking in rainy weather, comprising the following steps: S1: Based on the temperature and humidity sensors, the temperature and humidity data of multiple locations in the smoke-loading room of the intensive curing barn are collected and analyzed in real time, the impact of rainy weather on the temperature and humidity fluctuations in the smoke-loading room of the intensive curing barn is evaluated, and the changing trend of temperature and humidity is identified to generate temperature and humidity monitoring data; S2: Based on the temperature and humidity monitoring data, analyze the mutual influence and dependence between temperature and humidity, and generate interaction analysis results; S3: Using the interaction analysis results, evaluate the relationship between the power input and temperature and humidity changes of the baking equipment, analyze the temperature and humidity adjustment efficiency of multiple baking equipment, and form adjustment efficiency evaluation data; S4: Based on the regulation efficiency evaluation data, the infrared response characteristics of various tobacco leaf compounds are analyzed online using infrared spectroscopy sensors. By real-time monitoring of tobacco leaves, the content changes of various compounds are identified and chemical composition monitoring records are generated; S5: Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time, the tobacco leaf quality requirements at multiple baking stages are considered, the ambient temperature and humidity that need to be adjusted are analyzed, and the temperature and humidity adjustment requirements information is formulated; S6: Based on the temperature and humidity adjustment demand information, combined with the mutual influence relationship between temperature and humidity, and considering the rainy environmental conditions, the control parameters of the baking equipment are monitored and adjusted in real time to generate the baking temperature and humidity control records.

[0020] The temperature and humidity monitoring data include temperature change amplitude information, humidity change amplitude information, and temperature and humidity change trend chart; the interaction analysis results include the sensitivity index of temperature to humidity regulation, the response time of humidity to temperature, and the interdependence coefficient of temperature and humidity regulation; the regulation efficiency evaluation data include the energy efficiency grade of baking equipment, power regulation response speed, and temperature and humidity control energy consumption ratio information; the chemical composition monitoring records include the infrared absorption peak of characteristic compounds, the change trend of compound content, and the chemical reaction rate analysis results; the temperature and humidity adjustment demand information includes temperature demand analysis results, humidity control level indicators, and baking stage information; the baking temperature and humidity control records include real-time data of temperature and humidity in the smoke loading room of the intensive baking room, temperature and humidity matching data, and equipment adjustment parameter configuration.

[0021] See also Figure 2 Based on the temperature and humidity sensors, the temperature and humidity data of multiple locations in the dense smoke-curing room are collected and analyzed in real time, the impact of rainy weather on the temperature and humidity fluctuations in the dense smoke-curing room is evaluated, and the trend of temperature and humidity changes is identified. The specific steps for generating temperature and humidity monitoring data are as follows: S101: Based on the temperature and humidity sensors, considering the coverage and monitoring efficiency, deploy temperature and humidity sensors at multiple locations in the smoke loading room of the dense curing room, collect the temperature and humidity data of the smoke loading room in real time, obtain the real-time temperature and humidity data, and establish the deployment record of the temperature and humidity sensors.

[0022] In this embodiment, the specific operation process of sub-step S101 is: based on the temperature and humidity sensors, considering the coverage and monitoring efficiency, deploy temperature and humidity sensors at multiple locations in the dense curing room, evaluate the environmental characteristics of multiple locations in the dense curing room, including corners, centers and near window areas, select the optimal type and quantity of temperature and humidity sensors according to the spatial layout and expected data coverage, calculate the required number of temperature and humidity sensors and deploy the temperature and humidity sensors, perform real-time data collection and upload, compile the deployment location and performance parameters of each temperature and humidity sensor, form a temperature and humidity sensor deployment record table, use the temperature and humidity sensor efficiency calculation formula to evaluate the efficiency of the temperature and humidity sensor layout, ensure the comprehensiveness and accuracy of the monitoring data, and establish a temperature and humidity sensor deployment record.

[0023] The temperature and humidity sensor efficiency calculation formula is: ; in, is the efficiency percentage, represents the actual coverage area, is the number of temperature and humidity sensors actually used, The number of temperature and humidity sensors calculated theoretically.

[0024] S102: Based on the deployment records of the temperature and humidity sensors, by comparing the data fluctuations at multiple time points and locations, analyzing and identifying the impact of rainy weather on the data fluctuations, and generating temperature and humidity fluctuation information.

[0025] In this embodiment, the specific operation process of sub-step S102 is: based on the deployment record of the temperature and humidity sensor, by comparing the data fluctuations at multiple time points and locations, collecting the temperature and humidity data at multiple time points, and cleaning the data to exclude outliers, using the time series analysis method to compare the data differences of different temperature and humidity sensors in rainy weather and sunny weather, evaluate the impact of rainy weather on temperature and humidity, use the moving average method to smooth the data to better display trends and periodic changes, analyze the obtained data fluctuation information, calculate the data stability of each location and time point through the data stability analysis formula, identify the fluctuations in the data, and generate temperature and humidity fluctuation information.

[0026] The data stability analysis formula is: ; in, Indicates the stability of the data. Indicates The temperature or humidity value of each data point, represents the average of these data points, is the total number of data points.

[0027] S103: Based on the temperature and humidity fluctuation information, evaluate and predict the temperature and humidity change trend, identify the temperature and humidity change pattern in rainy weather, and generate temperature and humidity monitoring data.

[0028] In this embodiment, the specific operation process of sub-step S103 is: based on the temperature and humidity fluctuation information, evaluate and predict the temperature and humidity change trend, use regression analysis to determine the change trend of temperature and humidity data, identify the temperature and humidity change rules during rainy weather by analyzing the relationship between historical data and weather patterns, combine short-term and long-term data, and use the weighted moving average method to refine the trend forecast, use the temperature and humidity prediction model according to the analysis results, calculate the expected temperature and humidity range in the future, use the temperature and humidity prediction model to predict temperature and humidity changes, and generate temperature and humidity monitoring data.

[0029] The prediction model formula for temperature and humidity is: ; in, To predict the temperature or humidity at the time, is the temperature or humidity at the previous moment, is the historical average temperature or humidity, is the weight coefficient of temperature and humidity at the previous moment, which is used to measure the impact of historical data on future predictions. is the weight coefficient of the historical average temperature and humidity, which is used to adjust the contribution of the long-term trend to the prediction model. is the weight coefficient of the rainy weather impact factor, which is used to indicate the direct impact of rainy weather on temperature and humidity changes. is the influencing factor of rainy weather.

[0030] See also Figure 3 ,Based on the temperature and humidity monitoring data, the mutual influence and dependence between temperature and humidity are analyzed, and the steps to generate the interaction analysis results are as follows: S201: Based on the temperature and humidity monitoring data, analyze the impact of ambient temperature changes on humidity, record the humidity adjustment requirements caused by temperature changes, and generate impact relationship analysis data.

[0031] In this embodiment, the specific operation process of sub-step S201 is: based on the temperature and humidity monitoring data, a correlation analysis is performed on the temperature and humidity data in the environment through statistical methods to determine the direct impact of temperature changes on humidity, and a linear regression model is used to calculate the relationship coefficient between temperature changes and humidity responses, and the average adjustment range of humidity per degree of temperature change is evaluated. According to the model results, the humidity adjustment requirements of each monitoring point under the target temperature change are recorded, and the temperature and humidity impact model is used to record and predict the impact of temperature changes on humidity, and generate impact relationship analysis data.

[0032] The formula for the temperature-humidity effect model is: ; in, Indicates the humidity adjustment value. represents the temperature change, is the coefficient of the effect of temperature change on humidity, Represents the model error.

[0033] S202: Based on the impact relationship analysis data, evaluate the impact of humidity changes on temperature, record the temperature adjustment requirements caused by humidity changes, and generate humidity impact evaluation information.

[0034] In this embodiment, the specific operation process of sub-step S202 is: based on the impact relationship analysis data, use the reverse linear regression model to evaluate the feedback effect of humidity changes on ambient temperature, obtain the temperature adjustment requirements corresponding to each unit humidity change by calculation, record the temperature adjustment requirements of multiple monitoring points under different humidity conditions, and use the humidity on temperature impact model to evaluate the temperature adjustment requirements caused by humidity changes, and generate humidity impact assessment information.

[0035] The formula for the humidity-temperature effect model is: ; in, Indicates the temperature adjustment value. Indicates the humidity change. is the coefficient of humidity change on temperature, Represents the model error.

[0036] S203: Based on the humidity impact assessment information, assess the mutual impact relationship and dependency between temperature and humidity, and generate an interaction analysis result.

[0037] In this embodiment, the specific operation process of sub-step S203 is: based on the humidity impact assessment information, use the multivariate statistical analysis method to evaluate the mutual influence relationship between temperature and humidity, identify the mutual dependence by analyzing the covariate data of temperature and humidity, and quantitatively describe the mutual influence between temperature and humidity according to the statistical model results. Use the temperature and humidity interaction model to analyze the mutual influence relationship and dependency between temperature and humidity, and generate the interaction analysis results.

[0038] The formula of the temperature and humidity interaction model is: ; in, represents the comprehensive evaluation value of the interaction between temperature and humidity, and Represent the influence values ​​of temperature and humidity respectively, are model parameters, Represents the interaction term between temperature and humidity.

[0039] See also Figure 4, using the interaction analysis results, evaluate the relationship between the power input and temperature and humidity changes of the baking equipment, analyze the temperature and humidity adjustment efficiency of multiple baking equipment, and form the adjustment efficiency evaluation data in the following steps: S301: Based on the interaction analysis results, the response time and adjustment range of multiple baking devices under differentiated environmental conditions are analyzed to generate device response characteristic data.

[0040] In this embodiment, the specific operation process of sub-step S301 is: based on the interaction analysis results, collect performance data of multiple baking equipment under different environmental conditions, including response time and adjustment range, compare the response differences of baking equipment under differentiated environmental conditions through data analysis methods, quantitatively evaluate the adjustment capability and reaction speed for each baking equipment, determine the optimal performance under the target environment, use the response characteristic analysis model to analyze the performance changes of baking equipment under differentiated environmental conditions, and generate equipment response characteristic data.

[0041] The formula of the response characteristic analysis model is: ; in, Indicates the response characteristic value of the baking equipment, represents the response time coefficient, represents the environmental condition difference index, Indicates the adjustment range coefficient.

[0042] S302: Based on the device response characteristic data, the power consumption and temperature and humidity adjustment efficiency of multiple baking devices under differentiated temperature and humidity changes are calculated to generate device efficiency data.

[0043] In this embodiment, the specific operation process of sub-step S302 is: based on the equipment response characteristic data, the power consumption of multiple baking equipment under differentiated temperature and humidity change conditions is calculated, and the working efficiency of the baking equipment under the target temperature and humidity conditions is evaluated, including the energy consumption ratio required for temperature and humidity adjustment. Through energy consumption efficiency comparison, the performance levels of multiple baking equipment are determined, and the power consumption and temperature and humidity adjustment efficiency of multiple baking equipment under differentiated environmental conditions are calculated using the equipment efficiency data calculation model to generate equipment efficiency data.

[0044] The formula for the equipment efficiency data calculation model is: ; in, Indicates equipment efficiency data, Indicates the efficiency coefficient of baking equipment, and are the influence coefficients of temperature and humidity changes on power consumption, and Represent the changes in temperature and humidity respectively. Indicates basic energy consumption.

[0045] S303: Based on the equipment efficiency data, considering the mutual influence and dependency between temperature and humidity, calculating the parameter configuration of various temperature and humidity adjustment requirements, and generating adjustment efficiency evaluation data.

[0046] In this embodiment, the specific operation process of sub-step S303 is: based on the equipment efficiency data, integrate the mutual influence and dependency between temperature and humidity, determine various temperature and humidity adjustment requirements, calculate the parameter configuration of various temperature and humidity adjustment requirements, including baking equipment settings and operating parameters, evaluate the adjustment efficiency by simulating the operation of the baking equipment under differentiated parameter configurations, use the adjustment efficiency evaluation model to evaluate the adjustment efficiency under differentiated parameter configurations, and generate adjustment efficiency evaluation data.

[0047] The formula of the regulation efficiency evaluation model is: ; in, represents the evaluation value of regulation efficiency, is the efficiency adjustment coefficient, and are the temperature and humidity adjustment parameters, and Respectively represent the adjusted temperature and humidity, Indicates the adjusted base deviation.

[0048] See also Figure 5 Based on the regulation efficiency evaluation data, the infrared response characteristics of various tobacco leaf compounds are analyzed online using infrared spectroscopy sensors. By real-time monitoring of tobacco leaves, the content changes of various compounds are identified and the steps for generating chemical composition monitoring records are as follows: S401: Based on the regulation efficiency evaluation data, the spectral responses of various tobacco leaf compounds are collected and analyzed using an infrared spectral sensor, the spectral data are recorded, and tobacco leaf spectral recording data is generated.

[0049] In this embodiment, the specific operation process of sub-step S401 is: based on the adjustment efficiency evaluation data, use infrared spectral sensors to perform qualitative and quantitative analysis on the compounds in the tobacco leaves, implement multi-point sampling to increase the representativeness of the spectral data, collect and record spectral data of the samples, and locate and calculate the spectral peaks of the absorption peaks of the key compounds in the tobacco leaves. Quantitative analysis is performed through the calibration relationship between the spectral peak area and the compound concentration, and the spectral analysis model is used to calculate the concentrations of various compounds to generate tobacco leaf spectral recording data.

[0050] The formula of the spectral analysis model is: ; in, For the wavelength The absorbance at is the molar absorption coefficient, is the concentration of the compound, is the optical path length.

[0051] S402: Based on the tobacco leaf spectral recording data, identify the infrared response characteristics of multiple key compounds in the tobacco leaves, including nicotine and sugars, monitor the content changes of multiple compounds during the baking process, and generate compound content change data.

[0052] In this embodiment, the specific operation process of sub-step S402 is: based on the tobacco leaf spectral recording data, the infrared spectral response characteristics of nicotine and multiple key sugar compounds are identified and analyzed, and the standard spectral library comparison technology is used to identify the types of compounds through matching analysis, and the content changes of multiple compounds during the baking process are monitored. Regular sampling is implemented, and the spectral data of each stage is recorded. Through the difference analysis method, the compound content change evaluation model is used to calculate the changes of the compounds during the baking process, and the compound content change data is generated.

[0053] The formula for the compound content change assessment model is: ; in, is the compound content change data, is the concentration of the compound after baking, This is the concentration before baking.

[0054] S403: Using the compound content change data, combined with the real-time temperature and humidity data, evaluate the change trends of the contents of multiple compounds and generate chemical composition monitoring records.

[0055] In this embodiment, the specific operation process of sub-step S403 is: using compound change data, combined with real-time temperature and humidity data, adopting trend analysis method to evaluate the change trend of the content of multiple compounds, collecting temperature and humidity data, combining chemical analysis results with environmental factors through data fusion technology, constructing a content change trend model, estimating the impact of environmental factors on compound changes, and generating chemical composition monitoring records.

[0056] The formula of the content change trend model is: ; in, Indicates at time The change of compound content when represents the temperature at the corresponding time, Indicates humidity, is the baseline offset, which is used to indicate the initial estimated value of the compound content when there is no influence of external temperature and humidity changes. is the temperature coefficient, which is used to measure the effect of temperature change on the change of compound content. It is the humidity coefficient, which is used to measure the effect of humidity change on the change of compound content, indicating the corresponding change of compound content for every unit change of humidity.

[0057] See also Figure 6 Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time. The tobacco leaf quality requirements at multiple baking stages are considered, and the ambient temperature and humidity that need to be adjusted are analyzed. The specific steps for formulating the temperature and humidity adjustment requirements information are as follows: S501: Based on the chemical composition monitoring records, the content data of multiple key compounds are analyzed and compared with the quality standards to predict and evaluate the quality of tobacco leaves during the baking process and generate quality level analysis results.

[0058] In this embodiment, the specific operation process of sub-step S501 is: based on the chemical composition monitoring records, the content of nicotine, sugars and other key compounds in tobacco leaves is analyzed, and the actual monitoring data is compared with the industry quality standards using statistical analysis methods. The compound content exceeding the normal range is identified through deviation analysis, and the quality evaluation model is used to calculate the quality score. The tobacco leaf quality is evaluated by calculating the square difference between the target and actual content, and the quality level analysis results are generated.

[0059] The formula of the quality assessment model is: ; in, represents the quality score, is the weight coefficient, is the target compound content, The actual compound content.

[0060] S502: Based on the quality level analysis results, by analyzing the tobacco leaf quality requirements required in multiple baking stages, the deviation between the baking environment and the ideal quality target is evaluated in real time, and the adjustment target recognition result is generated.

[0061] In this embodiment, the specific operation process of sub-step S502 is: based on the quality level analysis results, considering the requirements for tobacco leaf quality in multiple baking stages, using a real-time data monitoring system to continuously evaluate the baking environment, and calculating the deviation between the actual environment and the ideal quality target through a deviation analysis model to generate an adjustment target identification result.

[0062] The formula for the deviation analysis model is: ; in, Indicates the deviation between the actual environment and the ideal quality target. is the baseline deviation, is the deviation adjustment factor, It is the real-time environment parameter.

[0063] S503: Based on the adjustment target identification result, considering the variation trend of tobacco leaf compounds under various temperature and humidity conditions, identifying the temperature and humidity parameters that need to be adjusted, and generating temperature and humidity adjustment demand information.

[0064] In this embodiment, the specific operation process of sub-step S503 is: based on the adjustment target identification result, analyze the impact of temperature and humidity on the changes in tobacco leaf compounds, combine trend analysis technology, consider historical and predicted data, use the environmental adjustment model to determine the temperature and humidity parameters that need to be adjusted, and generate temperature and humidity adjustment demand information.

[0065] The formula of the environmental regulation model is: ; in, Indicates the adjusted temperature, is the baseline adjustment factor, which is used to represent the basic temperature adjustment required when there is no change in external temperature or humidity. is the humidity adjustment coefficient, which reflects the direct impact of humidity changes on temperature adjustment. is the temperature adjustment coefficient, indicating the impact of temperature changes on the adjustment strategy. Indicates the change demand of humidity, Indicates the change in temperature required.

[0066] See also Figure 7 Based on the temperature and humidity adjustment demand information, combined with the mutual influence relationship between temperature and humidity, and considering the rainy environment conditions, the control parameters of the baking equipment are monitored and adjusted in real time. The steps to generate the baking temperature and humidity control record are as follows: S601: Based on the temperature and humidity adjustment demand information, real-time monitoring of temperature and humidity data of multiple areas in the smoke-loading room of the dense baking room under rainy conditions is performed, and control parameters are adjusted to match the baking demand, and control parameter adjustment records are generated.

[0067] In this embodiment, the specific operation process of sub-step S601 is: based on the temperature and humidity adjustment demand information, use temperature and humidity sensors to monitor the temperature and humidity of multiple areas in the smoke loading room of the intensive baking room in real time under rainy conditions, collect data through the environmental monitoring system, and use the parameter adjustment model to calculate and adjust the control parameters of the smoke loading room of the intensive baking room to ensure that the real-time adjustment of the control parameters matches the baking requirements and generate a control parameter adjustment record.

[0068] The formula of the parameter adjustment model is: ; in, represents the adjusted control parameters, is the baseline adjusted value, is the humidity adjustment factor, is the temperature adjustment factor, Indicates the monitored humidity data. Indicates the monitored temperature data.

[0069] S602: Based on the control parameter adjustment record, a fuzzy logic control method is used to adjust the temperature and humidity control parameters of the baking equipment in consideration of the mutual influence relationship between temperature and humidity and the temperature and humidity adjustment efficiency of the baking equipment, and an adjustment parameter optimization record is generated.

[0070] In this embodiment, the specific operation process of sub-step S602 is: based on the control parameter adjustment record, a fuzzy logic control method is adopted, the interaction between temperature and humidity and the adjustment efficiency of the baking equipment are considered, and a fuzzy rule set is constructed to adjust the control parameters according to the temperature and humidity data, match the baking equipment performance and environmental changes, and generate an adjustment parameter optimization record.

[0071] Fuzzy logic control method, according to the formula: ; Calculate the adjustment value of the temperature and humidity control parameters, where: It is the adjustment value of the control parameter, which is used to adjust the control system to achieve the predetermined environmental target. is the error between the target and actual temperature and humidity, which is used to measure the deviation between the current state and the target state. is the time variable, is the proportional gain, which is used to adjust the immediate effect of the error on the control output. is the integral gain, which is used to adjust the influence of the accumulated error on the control output. is the differential gain, which is used to adjust the effect of the error change rate on the control output. The environmental change rate indicates the speed at which environmental conditions change. It is used to measure the impact of changes in external conditions on the system. It is a stability index that measures the system's resistance to disturbances and is used to evaluate the stability of the system. is the weight coefficient of the environmental change rate, which is used to adjust the impact of the environmental change rate on the control decision. is the weight coefficient of the stability index, which is used to adjust the role of system stability in control decision-making. Indication error About time The differential of is used to calculate the rate of change of the error, Indication error About time The integral of is used to accumulate the total error, is the differential symbol, is the time differential, representing a small increment of time, and is used to calculate time-related rates of change. Error The differential of , which represents a small change in the error, is used to calculate the rate of change of the error over time.

[0072] The specific execution process of the formula is as follows: Through the real-time monitoring system, the temperature and humidity parameters of the current environment are obtained, and the environmental change rate is calculated at the same time and stability indicators , according to the preset ratio ,integral ,differential Gain, and the rate of change of the newly introduced environment and stability indicators Weight coefficient, using fuzzy logic control algorithm, obtain multiple parameters, substitute the parameters into the formula, and calculate the adjustment amount of temperature and humidity control parameters , which is used to adjust the baking equipment in real time to match the rainy environmental conditions, ensuring the color, aroma and overall quality of the tobacco leaves during the baking process.

[0073] S603: Based on the adjustment parameter optimization record, apply the temperature and humidity adjustment parameters, monitor the temperature and humidity adjustment effect in real time, evaluate the consistency with the baking requirements, and generate the baking temperature and humidity control record.

[0074] In this embodiment, the specific operation process of sub-step S603 is: based on the adjustment parameter optimization record, apply the temperature and humidity adjustment parameters, monitor the temperature and humidity of the baking environment and evaluate the adjustment effect, monitor the consistency with the baking requirements through the evaluation model, evaluate the effectiveness of the control parameter configuration, and generate a baking temperature and humidity control record.

[0075] The formula for evaluating the model is: ; in, Represents the consistency assessment value between environment and requirements. is the baseline coefficient of the temperature and humidity consistency evaluation model, which is used to indicate the initial evaluation value under the ideal adjustment state. To evaluate the humidity coefficient in the model, it is used to measure the impact of adjusted humidity on the consistency of baking requirements and reflect the contribution of humidity adjustment to quality control. To evaluate the temperature coefficient in the model, it is used to measure the effect of the adjusted temperature on the consistency of baking requirements, indicating the degree to which the effect of temperature adjustment matches the requirements. Indicates the adjusted humidity, Indicates the adjusted temperature.

[0076] See also Figure 8 The present invention also provides a rainy weather tobacco leaf baking temperature and humidity control system, which is used to execute the rainy weather tobacco leaf baking temperature and humidity control method, and the system includes: The environmental data acquisition module is based on temperature and humidity sensors, which monitor the temperature and humidity data of multiple locations in the dense smoke-curing room in real time, evaluate the impact of rainy weather on the temperature and humidity fluctuations in the dense smoke-curing room, and generate a temperature and humidity data set; The influence relationship analysis module calculates the interaction strength between temperature and humidity based on the temperature and humidity data set, evaluates the impact of ambient temperature changes on humidity, and generates dependency evaluation results; The regulation capability analysis module analyzes the relationship between the power input and temperature and humidity changes of the baking equipment based on the dependency evaluation results, evaluates the temperature and humidity regulation efficiency of multiple baking equipment, and generates equipment efficiency evaluation information; The real-time quality monitoring module uses infrared spectroscopy sensors to monitor the infrared response of tobacco leaf compounds in the baking process in real time based on equipment efficiency evaluation information, analyzes changes in compound content, predicts tobacco leaf quality during the baking process, and generates tobacco leaf quality prediction results; The parameter adjustment control module is based on the tobacco leaf quality prediction results, considers the mutual influence between temperature and humidity, monitors and adjusts the control parameters of the baking equipment in real time to match the rainy environment, and generates baking temperature and humidity control records.

[0077] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for controlling temperature and humidity of tobacco leaves during rainy weather baking, characterized in that: The following steps are involved: Based on the temperature and humidity sensors, the temperature and humidity data of multiple locations in the smoke-loading room of the intensive curing barn are collected and analyzed in real time, the impact of rainy weather on the temperature and humidity fluctuations in the smoke-loading room of the intensive curing barn is evaluated, and the trend of temperature and humidity changes is identified to generate temperature and humidity monitoring data; Based on the temperature and humidity monitoring data, analyze the mutual influence and dependence between temperature and humidity, and generate interaction analysis results; Using the interaction analysis results, evaluate the relationship between the power input and temperature and humidity changes of the baking equipment, analyze the temperature and humidity adjustment efficiency of multiple baking equipment, and form adjustment efficiency evaluation data; Based on the regulation efficiency evaluation data, infrared spectroscopy sensors are used to analyze the infrared response characteristics of various tobacco leaf compounds online. By real-time monitoring of tobacco leaves, changes in the content of various compounds are identified and chemical composition monitoring records are generated. Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time. The tobacco leaf quality requirements at multiple baking stages are considered, the ambient temperature and humidity that need to be adjusted are analyzed, and the temperature and humidity adjustment requirements information is formulated; Based on the temperature and humidity fluctuation information, the temperature and humidity adjustment demand information, combined with the mutual influence relationship between temperature and humidity, and considering the rainy environmental conditions, the control parameters of the baking equipment are monitored and adjusted in real time to generate the baking temperature and humidity control records.

2. The method for controlling temperature and humidity of tobacco leaves during rainy weather baking according to claim 1, characterized in that: The temperature and humidity monitoring data include temperature change amplitude information, humidity change amplitude information, and temperature and humidity change trend chart; the interaction analysis results include the sensitivity index of temperature to humidity regulation, the response time of humidity to temperature, and the interdependence coefficient of temperature and humidity regulation; the regulation efficiency evaluation data include the energy efficiency grade of baking equipment, power regulation response speed, and temperature and humidity control energy consumption ratio information; the chemical composition monitoring records include the infrared absorption peak of characteristic compounds, the change trend of compound content, and the chemical reaction rate analysis results; the temperature and humidity adjustment demand information includes temperature demand analysis results, humidity control level indicators, and baking stage information; the baking temperature and humidity control records include real-time data of temperature and humidity in the smoke loading room of the intensive baking room, temperature and humidity matching data, and equipment adjustment parameter configuration.

3. The method for controlling temperature and humidity of tobacco leaves during rainy weather baking according to claim 2, characterized in that: Based on the temperature and humidity sensors, the temperature and humidity data of multiple locations in the smoke-loading room of the intensive curing room are collected and analyzed in real time, the impact of rainy weather on the temperature and humidity fluctuations in the smoke-loading room of the intensive curing room is evaluated, and the trend of temperature and humidity changes is identified. The specific steps for generating temperature and humidity monitoring data are as follows: Based on temperature and humidity sensors, considering coverage and monitoring efficiency, temperature and humidity sensors are deployed at multiple locations in the smoke-loading room of the dense curing room to collect temperature and humidity data in real time, obtain real-time temperature and humidity data, and establish a deployment record of temperature and humidity sensors; Based on the deployment records of temperature and humidity sensors, the data fluctuations at multiple time points and locations are compared to analyze and identify the impact of rainy weather on data fluctuations, and generate temperature and humidity fluctuation information; Based on the temperature and humidity fluctuation information, evaluate and predict the changing trend of temperature and humidity data, identify the changing patterns of temperature and humidity in rainy weather, and generate temperature and humidity monitoring data.

4. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 3, characterized in that: Based on the temperature and humidity monitoring data, the mutual influence and dependence between temperature and humidity are analyzed, and the steps to generate the interaction analysis results are as follows: Based on the temperature and humidity monitoring data, analyze the impact of ambient temperature changes on humidity, record the humidity adjustment requirements caused by temperature changes, and generate impact relationship analysis data; Based on the impact relationship analysis data, evaluate the impact of humidity changes on temperature, record the temperature adjustment requirements caused by humidity changes, and generate humidity impact assessment information; Based on the humidity impact assessment information, the mutual influence relationship and dependency between temperature and humidity are evaluated, and the interaction analysis results are generated.

5. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 4, characterized in that: Using the interaction analysis results, the relationship between the power input and temperature and humidity changes of the baking equipment is evaluated, and the temperature and humidity adjustment efficiency of multiple baking equipment is analyzed. The specific steps for forming the adjustment efficiency evaluation data are as follows: Based on the interaction analysis results, the response time and adjustment range of multiple baking equipment under different environmental conditions are analyzed to generate equipment response characteristic data; Based on the equipment response characteristic data, the power consumption and temperature and humidity adjustment efficiency of multiple baking equipment under differentiated temperature and humidity changes are calculated to generate equipment efficiency data; Based on the equipment efficiency data, considering the mutual influence and dependency between temperature and humidity, the parameter configuration of various temperature and humidity adjustment requirements is calculated to generate adjustment efficiency evaluation data.

6. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 5, characterized in that: Based on the regulation efficiency evaluation data, the infrared response characteristics of various tobacco leaf compounds are analyzed online using infrared spectroscopy sensors. By real-time monitoring of tobacco leaves, the content changes of various compounds are identified and the steps for generating chemical composition monitoring records are as follows: Based on the regulation efficiency evaluation data, the spectral responses of various tobacco leaf compounds are collected and analyzed using an infrared spectral sensor, the spectral data are recorded, and tobacco leaf spectral recording data is generated; Based on the tobacco leaf spectrum recording data, the infrared response characteristics of multiple key compounds in tobacco leaves, including nicotine and sugars, are identified, the content changes of multiple compounds during the baking process are monitored, and compound content change data are generated; The compound content change data is used in combination with real-time temperature and humidity data to evaluate the changing trends of the contents of multiple compounds and generate chemical composition monitoring records.

7. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 6, characterized in that: Based on the chemical composition monitoring records, the tobacco leaf quality during the baking process is evaluated and predicted in real time. The tobacco leaf quality requirements at multiple baking stages are considered, and the environmental temperature and humidity that need to be adjusted are analyzed. The specific steps for formulating the temperature and humidity adjustment requirements information are as follows: Based on the chemical composition monitoring records, the content data of multiple key compounds are analyzed and compared with the quality standards to predict and evaluate the quality of tobacco leaves during the baking process and generate quality level analysis results; Based on the quality level analysis results, by analyzing the tobacco leaf quality requirements in multiple baking stages, the deviation between the baking environment and the ideal quality target is evaluated in real time, and the adjustment target identification results are generated; According to the adjustment target identification results, the changing trends of tobacco leaf compounds under various temperature and humidity conditions are considered, the temperature and humidity parameters that need to be adjusted are identified, and the temperature and humidity adjustment demand information is generated.

8. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 7, characterized in that: Based on the temperature and humidity adjustment demand information, combined with the mutual influence between temperature and humidity, and considering the rainy environment conditions, the control parameters of the baking equipment are monitored and adjusted in real time, and the steps for generating the baking temperature and humidity control record are as follows: Based on the temperature and humidity adjustment demand information, real-time monitoring of temperature and humidity data in multiple areas of the smoke-loading room in a densely populated curing room under rainy conditions is performed to adjust control parameters to match baking requirements and generate control parameter adjustment records; Based on the control parameter adjustment records, the fuzzy logic control method is used to consider the mutual influence between temperature and humidity and the temperature and humidity adjustment efficiency of the baking equipment, adjust the temperature and humidity control parameters of the baking equipment, and generate the adjustment parameter optimization record; Based on the adjustment parameter optimization record, apply the temperature and humidity adjustment parameters, monitor the temperature and humidity adjustment effect in real time, evaluate the consistency with the baking requirements, and generate the baking temperature and humidity control record.

9. The method for controlling temperature and humidity of tobacco leaves during rainy weather according to claim 8, characterized in that: The fuzzy logic control method is based on the formula: ； Calculate the adjustment value of the temperature and humidity control parameters, where: is the adjustment value of the control parameter, is the error between target and actual temperature and humidity, is the time variable, is the proportional gain, is the integral gain, is the differential gain, is the environmental change rate, is a stability indicator, is the weight coefficient of the environmental change rate, is the weight coefficient of the stability index, Indication error About time The differential of Indication error About time The integral of is the differential symbol, is the time differential, Error The differential of .

10. A rainy weather tobacco baking temperature and humidity control system, characterized by: According to the method for controlling temperature and humidity of tobacco leaf baking in rainy weather according to claim 9, the system comprises: The environmental data acquisition module is based on temperature and humidity sensors, which monitor the temperature and humidity data of multiple locations in the dense smoke-curing room in real time, evaluate the impact of rainy weather on the temperature and humidity fluctuations in the dense smoke-curing room, and generate a temperature and humidity data set; The influence relationship analysis module calculates the interaction strength between temperature and humidity based on the temperature and humidity data set, evaluates the impact of ambient temperature changes on humidity, and generates dependency evaluation results; The regulation capability analysis module analyzes the relationship between the power input and temperature and humidity changes of the baking equipment based on the dependency evaluation results, evaluates the temperature and humidity regulation efficiency of multiple baking equipment, and generates equipment efficiency evaluation information; The real-time quality monitoring module uses infrared spectroscopy sensors to monitor the infrared response of tobacco leaf compounds in the baking process in real time based on equipment efficiency evaluation information, analyzes changes in compound content, predicts tobacco leaf quality during the baking process, and generates tobacco leaf quality prediction results; The parameter adjustment control module is based on the tobacco leaf quality prediction results, considers the mutual influence between temperature and humidity, monitors and adjusts the control parameters of the baking equipment in real time to match the rainy environment, and generates baking temperature and humidity control records.

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