Temperature detection method and system for tobacco processing equipment

Abstract

The present application belongs to the field of equipment detection technology, and discloses a temperature detection method and system for tobacco processing equipment. The method determines the target time for obtaining the hot air valve opening and the ambient temperature by collecting the steam flow and water injection flow in real time when the tobacco processing equipment is running, and predicts the first temperature based on the hot air valve opening, the ambient temperature, all steam flows and all water injection flows. The final processing temperature of the tobacco processing equipment is obtained by combining the second temperature determined by the feed port temperature and the discharge port temperature. The method can not only combine the various operating parameters of the tobacco processing equipment to ensure the accuracy of internal temperature detection, but also effectively provide effective data support for subsequent preparation processes.

Description

Technical Field

[0001] The present application belongs to the field of equipment detection technology, and in particular relates to a temperature detection method and system for tobacco processing equipment. Background Art

[0002] Both the loosening and moistening process and the adding and moistening process are important steps in tobacco leaf processing on the cigarette shred production line. The loosening and moistening process primarily increases the moisture content and temperature of the tobacco leaves, thereby improving their processing resistance and loosening them. The adding and moistening process accurately and evenly applies liquid to the tobacco leaves, improving their sensory and physical properties while also increasing their moisture content and temperature. It can be seen that temperature stability or moisture content stability can directly affect the processing results of the process.

[0003] Due to the special environment of high temperature and high humidity inside the loosening and conditioning equipment, it is impossible to install a temperature sensor inside it. The current temperature detection method of the loosening and conditioning process is mainly through installing a probe temperature sensor (of course, it can also be an infrared thermometer) at the feed port or discharge port of the loosening and conditioning equipment to obtain the tobacco leaf temperature before the loosening and conditioning process and the tobacco leaf temperature after the loosening and conditioning process by indirect temperature measurement. However, this method cannot perform real-time detection of the tobacco leaf temperature during the loosening and conditioning process, and thus cannot provide effective data support for subsequent preparation processes. Summary of the Invention

[0004] This application aims to address the aforementioned technical drawbacks of the current temperature detection method for the loosening and conditioning process, which is mainly to install a probe-type temperature sensor (of course, an infrared thermometer can also be used) at the feed inlet or discharge outlet of the loosening and conditioning equipment to obtain the tobacco leaf temperature before and after the loosening and conditioning process by indirect temperature measurement. However, this method cannot detect the tobacco leaf temperature in real time during the loosening and conditioning process, and thus cannot provide effective data support for subsequent preparation processes. A temperature detection method and system for tobacco leaf processing equipment are proposed, and the technical solution is as follows:

[0005] In a first aspect, an embodiment of the present application provides a temperature detection method for tobacco processing equipment, comprising:

[0006] When the tobacco processing equipment is in operation, obtaining at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals;

[0007] Determine the target time based on all steam flows and all water injection flows, and obtain the hot air valve opening and ambient temperature of the tobacco processing equipment based on the target time;

[0008] Obtaining a first temperature based on the hot air valve opening, ambient temperature, total steam flow, and total water injection flow, and determining a second temperature based on the inlet temperature and outlet temperature of the tobacco processing equipment;

[0009] When it is detected that the difference between the first temperature and the second temperature is in a preset first interval, the first temperature is used as the processing temperature of the tobacco processing equipment.

[0010] In an optional solution of the first aspect, determining the target time according to all steam flow rates and all water injection flow rates includes:

[0011] Dividing all steam flows into at least two first flow sets, and calculating a first difference between any two steam flows in each first flow set; wherein each first flow set includes steam flows at three adjacent collection moments;

[0012] When it is detected that all first differences corresponding to any first flow set are within the preset second interval, the maximum acquisition time in the corresponding first flow set is used as the starting time, and all water injection flows are eliminated based on the starting time;

[0013] Dividing all the water injection flows after the elimination process into at least two second flow sets, and calculating a second difference between any two water injection flows in each second flow set; wherein each second flow set includes water injection flows at three adjacent collection moments;

[0014] When it is detected that all second difference values ​​corresponding to any second flow set are within the preset second interval, the maximum collection time in the corresponding second flow set is used as the target time.

[0015] In another optional solution of the first aspect, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the total steam flow rate, and the total water injection flow rate includes:

[0016] Screening out the steam flow rate corresponding to the starting moment and at least one adjacent steam flow rate from all steam flow rates, and taking the average value of all screened steam flow rates as the first target flow rate;

[0017] Screening out the water injection flow rate corresponding to the target time and at least one adjacent water injection flow rate from all water injection flow rates, and taking the average result of all the screened water injection flow rates as the second target flow rate;

[0018] The first temperature is obtained according to the hot air valve opening, the ambient temperature, the first target flow rate and the second target flow rate.

[0019] In another optional solution of the first aspect, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the first target flow rate, and the second target flow rate includes:

[0020] The hot air valve flow corresponding to the hot air valve opening is searched in a preset opening-flow database; wherein the preset opening-flow database includes at least two standard valve openings and a standard valve flow corresponding to each standard valve opening;

[0021] The hot air valve flow, ambient temperature, first target flow and second target flow are normalized respectively, and the normalized hot air valve flow, ambient temperature, first target flow and second target flow are input into the first deep learning model to obtain the first temperature; wherein, the first deep learning model is trained by at least two groups of standard valve flows and standard temperature sets corresponding to each group of standard valve flows, each group of standard valve flows includes standard hot air flow, standard steam flow and standard water injection flow, and each group of standard temperature sets includes standard ambient temperature and standard processing temperature.

[0022] In another optional solution of the first aspect, determining the second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment includes:

[0023] When it is detected that the difference between the temperature of the feed inlet and the temperature of the discharge outlet of the tobacco processing equipment is within a preset third interval, a weighted summation process is performed on the temperature of the feed inlet and the temperature of the discharge outlet according to a preset weight to obtain a second temperature;

[0024] When it is detected that the difference between the temperature of the feed port and the temperature of the discharge port of the tobacco processing equipment is not within the preset third interval, a temperature warning signal is sent to the user terminal.

[0025] In another optional solution of the first aspect, after setting the first temperature as the processing temperature of the tobacco processing equipment, the method further includes:

[0026] Acquire an image of tobacco leaves output from a discharge port of tobacco leaf processing equipment, and perform standardization processing on the image;

[0027] Extracting tobacco leaf texture features from the standardized image and inputting the tobacco leaf texture features into a second deep learning model to obtain the moisture content of the tobacco leaf; wherein the second deep learning model is trained using at least two standard texture features and a standard moisture content corresponding to each standard texture feature;

[0028] When it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, a valve adjustment signal is sent to the tobacco leaf processing equipment, so that the tobacco leaf processing equipment adjusts the steam valve opening and the water injection valve opening respectively.

[0029] In another optional solution of the first aspect, after setting the first temperature as the processing temperature of the tobacco processing equipment, the method further includes:

[0030] When it is detected that the discharge port temperature does not exceed the preset temperature threshold, the target valve opening is calculated according to the difference between the discharge port temperature and the preset temperature threshold;

[0031] The target valve opening is sent to the tobacco processing equipment so that the tobacco processing equipment controls the opening of the hot air valve to be consistent with the target valve opening.

[0032] In a second aspect, an embodiment of the present application provides a temperature detection system for tobacco processing equipment, comprising:

[0033] A first acquisition module is configured to acquire at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals when the tobacco processing equipment is in operation;

[0034] The second acquisition module is used to determine the target time according to all steam flow rates and all water injection flow rates, and obtain the hot air valve opening and ambient temperature of the tobacco processing equipment based on the target time;

[0035] a third acquisition module, configured to obtain a first temperature based on the hot air valve opening, the ambient temperature, all steam flows, and all water injection flows, and determine a second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment;

[0036] The temperature determination module is used to use the first temperature as the processing temperature of the tobacco processing equipment when it is detected that the difference between the first temperature and the second temperature is in a preset first interval.

[0037] In a third aspect, an embodiment of the present application further provides a temperature detection system for tobacco processing equipment, comprising a processor and a memory;

[0038] The processor is connected to the memory;

[0039] a memory for storing executable program code;

[0040] The processor runs the program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the temperature detection method of the tobacco processing equipment provided by the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a computer storage medium, which stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, the temperature detection method of the tobacco processing equipment provided by the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect can be implemented.

[0042] In an embodiment of the present application, when temperature detection is performed on tobacco processing equipment, when the tobacco processing equipment is in operation, at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment are obtained according to preset time intervals; a target time is determined based on all steam flow rates and all water injection flow rates, and the hot air valve opening and ambient temperature of the tobacco processing equipment are obtained based on the target time; a first temperature is obtained based on the hot air valve opening, ambient temperature, all steam flow rates and all water injection flow rates, and a second temperature is determined based on the feed port temperature and the discharge port temperature of the tobacco processing equipment; when it is detected that the difference between the first temperature and the second temperature is in a preset first interval, the first temperature is used as the processing temperature of the tobacco processing equipment. By collecting the steam flow and water injection flow in real time during the operation of the tobacco processing equipment, the target time for obtaining the hot air valve opening and the ambient temperature is determined, and the first temperature is predicted based on the hot air valve opening, the ambient temperature, all steam flows and all water injection flows. The second temperature determined by combining the inlet temperature and the outlet temperature is used to obtain the final processing temperature of the tobacco processing equipment. This can not only combine the various operating parameters of the tobacco processing equipment to ensure the accuracy and synchronization of internal temperature detection, but also effectively provide effective data support for subsequent preparation processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 This is an overall flow chart of a temperature detection method for tobacco processing equipment provided in an embodiment of the present application;

[0045] Figure 2 A schematic structural diagram of a temperature detection system for tobacco processing equipment provided in an embodiment of the present application;

[0046] Figure 3 A structural schematic diagram of a temperature detection system for another tobacco processing equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application.

[0048] In the following introduction, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present application. Different embodiments can be replaced or combined, so the present application can also be considered to include all possible combinations of the same and / or different embodiments described. Therefore, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present application should also be considered to include embodiments containing one or more of all other possible combinations of A, B, C, and D, even though the embodiment may not be clearly described in the following text.

[0049] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the elements described without departing from the scope of the present application. Various examples may appropriately omit, replace, or add various processes or components. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted, or combined. In addition, features described in some examples may be combined in other examples.

[0050] See also Figure 1 , Figure 1 The figure shows an overall flow chart of a temperature detection method for tobacco processing equipment provided in an embodiment of the present application.

[0051] like Figure 1 As shown, the temperature detection method of the tobacco processing equipment may include at least the following steps:

[0052] Step 102: When the tobacco processing equipment is in operation, at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment are obtained at preset time intervals.

[0053] In the embodiments of the present application, the temperature detection method of tobacco leaf processing equipment can be applied to, but is not limited to, a control terminal. The control terminal can establish a connection with the tobacco leaf processing equipment to deduce the processing temperature of the tobacco leaf processing equipment during the heating and humidification process of the tobacco leaf based on the detection data fed back in real time by the various sensors configured by the tobacco leaf processing equipment. Here, the tobacco leaf processing equipment can be, but is not limited to, a loosening and rehumidification device or a feeding and moistening device for increasing the moisture content and temperature of the leaves. The types of sensors configured therein can include, but are not limited to, temperature sensors, flow sensors, and control valves to collect detection data at corresponding positions in real time when the tobacco leaf processing equipment is in normal operation.

[0054] Among them, taking the tobacco processing equipment as a loosening and conditioning equipment as an example, the temperature sensors configured therein can be, but are not limited to being set at the feed port, the discharge port and the workshop where it is located, so as to respectively obtain the tobacco leaf temperature received by the loosening and conditioning equipment during operation, the tobacco leaf temperature output after the loosening and conditioning treatment and the ambient temperature in the workshop; the flow sensors configured therein can be, but are not limited to being set in the pipe used for steam humidification output of tobacco leaves and in the pipe used for micro-mist humidification output of tobacco leaves, so as to respectively obtain multiple steam flow rates and multiple water injection flow rates, and valves for adjusting the output flow rate can also be provided in the steam output pipe and the micro-mist output pipe to adjust the corresponding valve opening according to the control signal sent by the control terminal; the control valves configured therein can be, but are not limited to being set in the pipe used for hot air heating treatment of tobacco leaves, so as to obtain the corresponding valve opening of the pipe when outputting hot air.

[0055] It can be understood that when the control terminal detects the processing temperature in the loosening and rehumidification equipment, it can determine the target time for obtaining the hot air valve opening and the ambient temperature through the steam flow and water injection flow collected in real time when the tobacco processing equipment is running, and predict the first temperature based on the hot air valve opening, ambient temperature, all steam flows and all water injection flows, and combine the second temperature determined by the feed port temperature and the discharge port temperature to obtain the final processing temperature of the tobacco processing equipment. It can not only combine the various operating parameters of the tobacco processing equipment to ensure the accuracy and synchronization of internal temperature detection, but also effectively provide effective data support for subsequent preparation processes.

[0056] Specifically, when performing temperature detection on tobacco leaf processing equipment, the control terminal can, but is not limited to, determine the current state of the tobacco leaf processing equipment based on the signal emitted by the tobacco leaf processing equipment or the instruction input manually, and when it is detected that the tobacco leaf processing equipment is currently in a normal operating state, it indicates that the tobacco leaf processing equipment has performed heating and humidification processing on the tobacco leaves, and then a data request signal can be sent to all flow sensors configured for the tobacco leaf processing equipment to receive multiple steam flow rates and multiple water injection flow rates collected in real time by the multiple flow sensors according to preset time intervals. It is understandable that when it is detected that the tobacco leaf processing equipment is not yet in a normal operating state, the control terminal can continue to detect the signal emitted by the tobacco leaf processing equipment or the instruction input manually in real time, without limitation to this.

[0057] Here, all flow sensors configured in the tobacco processing equipment can be, but are not limited to, set in pipes for steam humidification output of tobacco leaves and pipes for micro-mist humidification output of tobacco leaves, wherein the flow sensor in the steam output pipe can collect the steam flow in real time according to a preset time interval, and feed back the real-time collected steam flow to the control terminal; the flow sensor in the micro-mist output pipe can collect the water injection flow in real time according to the same preset time interval, and feed back the real-time collected water injection flow to the control terminal.

[0058] Step 104: determine a target time according to all steam flows and all water injection flows, and obtain the hot air valve opening and ambient temperature of the tobacco processing equipment based on the target time.

[0059] Specifically, after obtaining multiple steam flow rates and multiple water injection flow rates collected in real time by the flow sensor, the control terminal can, but is not limited to, determine the target time when the steam output and the micro-mist output are both in a stable state based on the multiple steam flow rates and multiple water injection flow rates, that is, the data collected corresponding to the target time is more reliable, and a data request signal can be sent to the control valve and temperature sensor configured for the tobacco processing equipment to receive the hot air valve opening corresponding to the control valve at the target time, and the ambient temperature collected by the temperature sensor at the target time.

[0060] Here, the control valve can be, but is not limited to being, set in a pipe used for hot air heating treatment of tobacco leaves. The hot air valve opening corresponding to the target moment can be understood as the valve opening pre-set by the tobacco processing equipment, or the valve opening adjusted according to a preset automatic control program; the temperature sensor can be, but is not limited to being set in the workshop where the tobacco processing equipment is located, for collecting the real-time ambient temperature of the tobacco processing equipment when it is in operation.

[0061] As an option in the embodiment of the present application, determining the target time according to all steam flows and all water injection flows includes:

[0062] Dividing all steam flows into at least two first flow sets, and calculating a first difference between any two steam flows in each first flow set; wherein each first flow set includes steam flows at three adjacent collection moments;

[0063] When it is detected that all first differences corresponding to any first flow set are within the preset second interval, the maximum acquisition time in the corresponding first flow set is used as the starting time, and all water injection flows are eliminated based on the starting time;

[0064] Dividing all the water injection flows after the elimination process into at least two second flow sets, and calculating a second difference between any two water injection flows in each second flow set; wherein each second flow set includes water injection flows at three adjacent collection moments;

[0065] When it is detected that all second difference values ​​corresponding to any second flow set are within the preset second interval, the maximum collection time in the corresponding second flow set is used as the target time.

[0066] Specifically, because tobacco processing equipment generally first introduces high-temperature, high-pressure steam and then forms a fine mist by injecting water when humidifying tobacco leaves, the steady-state moment of the steam flow rate is earlier than the steady-state moment of the water injection flow rate. Furthermore, after obtaining multiple steam flow rates and multiple water injection flow rates, the control terminal may also, but is not limited to, divide all steam flow rates into multiple first flow sets based on the collection time corresponding to each steam flow rate, so that each first flow set includes steam flow rates at three adjacent collection times. For example, taking all steam flow rates as A, B, C, D, and E as an example, all the divided first flow sets can be represented as ABC, BCD, and CDE, respectively.

[0067] Then, after dividing into multiple first flow sets, the control terminal can perform difference calculation on any two steam flow rates in each first flow set to obtain the corresponding first difference, and when it is detected that all the first differences corresponding to any first flow set are in the preset second interval, it indicates that the current steam flow has stabilized, and then the maximum collection moment in the corresponding first flow set can be used as the starting moment, and all the injection flows obtained in real time can be screened according to the starting moment, that is, some injection flows whose collection moments are before the starting moment are eliminated from all the injection flows.

[0068] Then, after eliminating all water injection flows, the control terminal may continuously obtain one or more water injection flows collected by the flow sensor at preset time intervals, and may divide all current water injection flows into multiple second flow sets, such that each second flow set includes water injection flows at three adjacent collection moments. It is understood that after the steam flow rate stabilizes, in order to ensure humidification stability of the tobacco processing equipment throughout its operation, it is also possible, but not limited to, to continuously obtain one or more steam flow rates collected by the flow sensor at preset time intervals, and determine in real time whether each steam flow rate exceeds a preset steam flow threshold, thereby ensuring the humidification effect of the tobacco leaves.

[0069] Then, after dividing into multiple second flow sets, the control terminal can calculate the difference between any two water injection flows in each second flow set to obtain the corresponding second difference, and when it is detected that all the second differences corresponding to any second flow set are in the preset second interval, it indicates that the current water injection flow has stabilized, and the maximum collection time in the corresponding second flow set can be used as the target time.

[0070] Step 106: Obtain a first temperature based on the hot air valve opening, ambient temperature, all steam flows, and all water injection flows, and determine a second temperature based on the inlet temperature and outlet temperature of the tobacco processing equipment.

[0071] Specifically, after obtaining the hot air valve opening and ambient temperature corresponding to the target moment, the control terminal can, but is not limited to, filter out the steam flow corresponding to the above-mentioned starting moment from all steam flows, and can perform mean calculation on the steam flow and one or two adjacent steam flows, and use the mean calculation result as the first target flow, that is, the stable steam flow corresponding to the steam output pipe of the tobacco processing equipment when humidifying tobacco leaves.

[0072] Furthermore, the control terminal can also filter out the water injection flow corresponding to the target moment mentioned above from all water injection flows, and can perform mean calculation on the water injection flow and one or two adjacent water injection flows, and use the mean calculation result as the second target flow, that is, the stable water injection flow corresponding to the micro-mist output pipe of the tobacco processing equipment when humidifying tobacco leaves.

[0073] Furthermore, after obtaining the hot air valve opening and ambient temperature corresponding to the target time, the control terminal may also, but is not limited to, query a preset opening-flow rate database to determine the hot air valve flow rate corresponding to the hot air valve opening, thereby converting the hot air valve opening into flow rate to facilitate subsequent data processing. Here, the preset opening-flow rate database may include at least two standard valve openings and a standard valve flow rate corresponding to each standard valve opening.

[0074] Furthermore, after converting the hot air valve opening into the hot air valve flow, in order to ensure data consistency, the control terminal may also, but is not limited to, normalize the hot air valve flow, ambient temperature, first target flow, and second target flow respectively, and input the normalized hot air valve flow, ambient temperature, first target flow, and second target flow into the first deep learning model to predict the first temperature. Here, the first deep learning model can be understood as a neural network structure well known in the art, which can be trained by multiple sets of standard valve flows and standard temperature sets corresponding to each set of standard valve flows, each set of standard valve flows can include standard hot air flow, standard steam flow, and standard water injection flow, each set of standard temperature sets includes standard ambient temperature and standard processing temperature, and the standard hot air flow, standard steam flow, standard water injection flow, standard ambient temperature, and standard processing temperature mentioned in the embodiments of the present application can all be obtained by manual statistical analysis.

[0075] Furthermore, after predicting the first temperature of the tobacco processing equipment when heating and humidifying the tobacco leaves through the first deep learning model, the control terminal can also, but is not limited to, send data request signals to the temperature sensors provided at the feed port and the discharge port of the tobacco processing equipment, respectively, to obtain the feed port temperature and the discharge port temperature collected in real time by the two temperature sensors, respectively, and can estimate the second temperature of the tobacco processing equipment when heating and humidifying the tobacco leaves based on the feed port temperature and the discharge port temperature, and then can combine the second temperature to judge the validity and accuracy of the first temperature predicted by the first deep learning model.

[0076] As another option of the embodiment of the present application, determining the second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment includes:

[0077] When it is detected that the difference between the temperature of the feed inlet and the temperature of the discharge outlet of the tobacco processing equipment is within a preset third interval, a weighted summation process is performed on the temperature of the feed inlet and the temperature of the discharge outlet according to a preset weight to obtain a second temperature;

[0078] When it is detected that the difference between the temperature of the feed port and the temperature of the discharge port of the tobacco processing equipment is not within the preset third interval, a temperature warning signal is sent to the user terminal.

[0079] Specifically, when estimating the second temperature of the tobacco leaf processing equipment when heating and humidifying the tobacco leaves based on the feed inlet temperature and the discharge port temperature, the control terminal can, but is not limited to, when detecting that the difference between the feed inlet temperature and the discharge port temperature is within a preset third interval, indicate that the discharge port temperature is within a normal temperature range, and then perform weighted summation processing on the feed inlet temperature and the discharge port temperature according to preset weights to estimate the second temperature. Here, the preset weights can be manually derived based on the collected historical feed inlet temperature, historical discharge port temperature, and historical processing temperature analysis, so that the second temperature calculated by the preset weights can effectively determine the accuracy and reliability of the first temperature.

[0080] It can be understood that when it is detected that the difference between the feed port temperature and the discharge port temperature is not in the preset third interval, it indicates that the discharge port temperature may currently be abnormal, and a temperature warning signal can be sent to the user terminal to notify manual inspection and processing of the tobacco processing equipment in a timely manner.

[0081] Step 108: When it is detected that the difference between the first temperature and the second temperature is in a preset first interval, the first temperature is used as the processing temperature of the tobacco processing equipment.

[0082] Specifically, after estimating the first temperature and the second temperature respectively, the control terminal can, but is not limited to, perform a difference calculation on the first temperature and the second temperature, so that when it is detected that the corresponding difference is in a preset first interval, it indicates that the difference between the first temperature and the second temperature is small. Since the temperature accuracy estimated by the first deep learning model is more reliable, the first temperature can be used as the processing temperature of the tobacco processing equipment, and multiple processing temperatures can be generated by the control terminal during the entire operation of the tobacco processing equipment to further judge the stability of the tobacco processing equipment when heating and humidifying tobacco leaves.

[0083] It should be noted that when it is detected that the corresponding difference is not within the preset first interval, it indicates that the difference between the first temperature and the second temperature is large. To ensure the accuracy of the results, the control terminal can re-determine the target time based on the multiple steam flow rates and multiple water injection flow rates currently obtained, and re-determine the first temperature and the second temperature with reference to the aforementioned embodiment until the corresponding difference is within the preset first interval. Of course, the control terminal can also retrain the first deep learning model mentioned above or manually reset the preset weights after detecting that the corresponding difference is not within the preset first interval, without limitation to this.

[0084] As another optional embodiment of the present application, after setting the first temperature as the processing temperature of the tobacco processing equipment, the method further includes:

[0085] Acquire an image of tobacco leaves output from a discharge port of tobacco leaf processing equipment, and perform standardization processing on the image;

[0086] Extracting tobacco leaf texture features from the standardized image and inputting the tobacco leaf texture features into a second deep learning model to obtain the moisture content of the tobacco leaf; wherein the second deep learning model is trained using at least two standard texture features and a standard moisture content corresponding to each standard texture feature;

[0087] When it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, a valve adjustment signal is sent to the tobacco leaf processing equipment, so that the tobacco leaf processing equipment adjusts the steam valve opening and the water injection valve opening respectively.

[0088] Specifically, in order to further ensure the heating and humidification effect of the tobacco processing equipment on the tobacco leaves, the control terminal can, after determining the processing temperature of the tobacco processing equipment for heating and humidifying the tobacco leaves, also but not limited to obtaining the tobacco leaf image at the discharge port of the tobacco processing equipment through an industrial camera, and standardizing the tobacco leaf image to ensure the accuracy of subsequent image analysis. Here, the annotation processing method can include but is not limited to size scaling, grayscale, denoising, etc., and is not limited to this.

[0089] Next, after normalizing the tobacco leaf image, the control terminal may also, but is not limited to, analyze the normalized image to extract tobacco leaf texture features. These texture features may then be input into a second deep learning model to predict the moisture content of the tobacco leaves output by the tobacco processing equipment. The second deep learning model may be a neural network structure well known in the art, trained using multiple standard texture features and the standard moisture content corresponding to each standard texture feature.

[0090] Then, after predicting the moisture content of the tobacco leaves, the control terminal can also determine whether the moisture content of the tobacco leaves currently output by the tobacco leaf processing equipment meets the requirements based on the moisture content of the tobacco leaves. For example, but not limited to, when it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, it indicates that the moisture content of the tobacco leaves currently output by the tobacco leaf processing equipment has not yet met the requirements. Then, a valve adjustment signal can be sent to the tobacco leaf processing equipment to enable the tobacco leaf processing equipment to adjust the steam valve opening and the water injection valve opening respectively, so as to quickly make the moisture content of the tobacco leaves output by the tobacco leaf processing equipment meet the requirements. It is understandable that when the moisture content of the tobacco leaves is less than the preset moisture content range, the tobacco leaf processing equipment can gradually increase the steam valve opening and the water injection valve opening by adjusting the valve opening in a step-by-step manner; when the moisture content of the tobacco leaves is greater than the preset moisture content range, the tobacco leaf processing equipment can also gradually reduce the steam valve opening and the water injection valve opening by adjusting the valve opening in a step-by-step manner.

[0091] As another optional embodiment of the present application, after setting the first temperature as the processing temperature of the tobacco processing equipment, the method further includes:

[0092] When it is detected that the discharge port temperature does not exceed the preset temperature threshold, the target valve opening is calculated according to the difference between the discharge port temperature and the preset temperature threshold;

[0093] The target valve opening is sent to the tobacco processing equipment so that the tobacco processing equipment controls the opening of the hot air valve to be consistent with the target valve opening.

[0094] Specifically, in order to further ensure the heating and humidification effect of the tobacco processing equipment on the tobacco leaves, the control terminal can, after determining the processing temperature of the tobacco processing equipment for heating and humidifying the tobacco leaves, also be able to, but not limited to, detect that the discharge port temperature does not exceed the preset temperature threshold, indicating that the current tobacco temperature output by the tobacco processing equipment has not met the requirements, and then, based on the temperature difference between the discharge port temperature and the preset temperature threshold, query the adjustment opening corresponding to the temperature difference in the preset temperature-opening database, and obtain the target valve opening based on the sum of the adjustment opening and the current opening of the hot air valve.

[0095] Then, after determining the target valve opening, the control terminal can send the target valve opening to the tobacco processing equipment, so that the tobacco processing equipment can promptly control the opening of the hot air valve to be consistent with the target valve opening, thereby achieving the purpose of quickly adjusting the tobacco temperature.

[0096] See also Figure 2 , Figure 2 A structural schematic diagram of a temperature detection system for tobacco processing equipment provided in an embodiment of the present application is shown.

[0097] like Figure 2 As shown, the temperature detection system of the tobacco processing equipment may include at least a first acquisition module 201, a second acquisition module 202, a third acquisition module 203 and a temperature determination module 204, wherein:

[0098] A first acquisition module 201 is configured to acquire at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals when the tobacco processing equipment is in operation;

[0099] The second acquisition module 202 is used to determine the target time according to all steam flow rates and all water injection flow rates, and obtain the hot air valve opening and ambient temperature of the tobacco processing equipment based on the target time;

[0100] The third acquisition module 203 is used to obtain the first temperature based on the hot air valve opening, the ambient temperature, the total steam flow rate, and the total water injection flow rate, and determine the second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment;

[0101] The temperature determination module 204 is configured to use the first temperature as the processing temperature of the tobacco processing equipment when it is detected that the difference between the first temperature and the second temperature is within a preset first interval.

[0102] In some possible embodiments, determining the target time according to all steam flows and all water injection flows includes:

[0103] Dividing all steam flows into at least two first flow sets, and calculating a first difference between any two steam flows in each first flow set; wherein each first flow set includes steam flows at three adjacent collection moments;

[0104] When it is detected that all first differences corresponding to any first flow set are within the preset second interval, the maximum acquisition time in the corresponding first flow set is used as the starting time, and all water injection flows are eliminated based on the starting time;

[0105] Dividing all the water injection flows after the elimination process into at least two second flow sets, and calculating a second difference between any two water injection flows in each second flow set; wherein each second flow set includes water injection flows at three adjacent collection moments;

[0106] When it is detected that all second difference values ​​corresponding to any second flow set are within the preset second interval, the maximum collection time in the corresponding second flow set is used as the target time.

[0107] In some possible embodiments, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the total steam flow rate, and the total water injection flow rate includes:

[0108] Screening out the steam flow rate corresponding to the starting moment and at least one adjacent steam flow rate from all steam flow rates, and taking the average value of all screened steam flow rates as the first target flow rate;

[0109] Screening out the water injection flow rate corresponding to the target time and at least one adjacent water injection flow rate from all water injection flow rates, and taking the average result of all the screened water injection flow rates as the second target flow rate;

[0110] The first temperature is obtained according to the hot air valve opening, the ambient temperature, the first target flow rate and the second target flow rate.

[0111] In some possible embodiments, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the first target flow rate, and the second target flow rate includes:

[0112] The hot air valve flow corresponding to the hot air valve opening is searched in a preset opening-flow database; wherein the preset opening-flow database includes at least two standard valve openings and a standard valve flow corresponding to each standard valve opening;

[0113] The hot air valve flow, ambient temperature, first target flow and second target flow are normalized respectively, and the normalized hot air valve flow, ambient temperature, first target flow and second target flow are input into the first deep learning model to obtain the first temperature; wherein, the first deep learning model is trained by at least two groups of standard valve flows and standard temperature sets corresponding to each group of standard valve flows, each group of standard valve flows includes standard hot air flow, standard steam flow and standard water injection flow, and each group of standard temperature sets includes standard ambient temperature and standard processing temperature.

[0114] In some possible embodiments, determining the second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment includes:

[0115] When it is detected that the difference between the temperature of the feed inlet and the temperature of the discharge outlet of the tobacco processing equipment is within a preset third interval, a weighted summation process is performed on the temperature of the feed inlet and the temperature of the discharge outlet according to a preset weight to obtain a second temperature;

[0116] When it is detected that the difference between the temperature of the feed port and the temperature of the discharge port of the tobacco processing equipment is not within the preset third interval, a temperature warning signal is sent to the user terminal.

[0117] In some possible embodiments, after setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes:

[0118] Acquire an image of tobacco leaves output from a discharge port of tobacco leaf processing equipment, and perform standardization processing on the image;

[0119] Extracting tobacco leaf texture features from the standardized image and inputting the tobacco leaf texture features into a second deep learning model to obtain the moisture content of the tobacco leaf; wherein the second deep learning model is trained using at least two standard texture features and a standard moisture content corresponding to each standard texture feature;

[0120] When it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, a valve adjustment signal is sent to the tobacco leaf processing equipment, so that the tobacco leaf processing equipment adjusts the steam valve opening and the water injection valve opening respectively.

[0121] In some possible embodiments, after setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes:

[0122] When it is detected that the discharge port temperature does not exceed the preset temperature threshold, the target valve opening is calculated according to the difference between the discharge port temperature and the preset temperature threshold;

[0123] The target valve opening is sent to the tobacco processing equipment so that the tobacco processing equipment controls the opening of the hot air valve to be consistent with the target valve opening.

[0124] Those skilled in the art will clearly understand that the technical solutions of the embodiments of the present application can be implemented with the help of software and / or hardware. "Unit" and "module" in this specification refer to software and / or hardware that can independently perform or cooperate with other components to perform specific functions, where the hardware can be, for example, a field-programmable gate array (FPGA) or an integrated circuit (IC).

[0125] See also Figure 3 , Figure 3 A structural schematic diagram of a temperature detection system for tobacco processing equipment provided in an embodiment of the present application is shown.

[0126] like Figure 3 As shown, the temperature detection system of the tobacco processing equipment may include at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 and at least one communication bus 302 .

[0127] The communication bus 302 may be used to implement the connection and communication between the above components.

[0128] The user interface 303 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0129] The network interface 304 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, and the like.

[0130] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the tobacco processing equipment's temperature detection system 300. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accessing data stored in the memory 305, the processor 301 executes various functions and processes data within the tobacco processing equipment's temperature detection system 300. Optionally, the processor 301 may be implemented in hardware using at least one of a DSP, FPGA, and PLA. The processor 301 may integrate one or a combination of a CPU, a GPU, and a modem. The CPU primarily handles the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0131] Among them, the memory 305 may include RAM and ROM. Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also be optionally at least one storage device located away from the aforementioned processor 301. As Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a temperature detection application program for tobacco processing equipment.

[0132] Specifically, the processor 301 may be used to call the temperature detection application of the tobacco processing equipment stored in the memory 305, and specifically perform the following operations:

[0133] When the tobacco processing equipment is in operation, obtaining at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals;

[0134] Determine the target time based on all steam flows and all water injection flows, and obtain the hot air valve opening and ambient temperature of the tobacco processing equipment based on the target time;

[0135] Obtaining a first temperature based on the hot air valve opening, ambient temperature, total steam flow, and total water injection flow, and determining a second temperature based on the inlet temperature and outlet temperature of the tobacco processing equipment;

[0136] When it is detected that the difference between the first temperature and the second temperature is in a preset first interval, the first temperature is used as the processing temperature of the tobacco processing equipment.

[0137] In some possible embodiments, determining the target time according to all steam flows and all water injection flows includes:

[0138] Dividing all steam flows into at least two first flow sets, and calculating a first difference between any two steam flows in each first flow set; wherein each first flow set includes steam flows at three adjacent collection moments;

[0139] When it is detected that all first differences corresponding to any first flow set are within the preset second interval, the maximum acquisition time in the corresponding first flow set is used as the starting time, and all water injection flows are eliminated based on the starting time;

[0140] Dividing all the water injection flows after the elimination process into at least two second flow sets, and calculating a second difference between any two water injection flows in each second flow set; wherein each second flow set includes water injection flows at three adjacent collection moments;

[0141] When it is detected that all second difference values ​​corresponding to any second flow set are within the preset second interval, the maximum collection time in the corresponding second flow set is used as the target time.

[0142] In some possible embodiments, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the total steam flow rate, and the total water injection flow rate includes:

[0143] Screening out the steam flow rate corresponding to the starting moment and at least one adjacent steam flow rate from all steam flow rates, and taking the average value of all screened steam flow rates as the first target flow rate;

[0144] Screening out the water injection flow rate corresponding to the target time and at least one adjacent water injection flow rate from all water injection flow rates, and taking the average result of all the screened water injection flow rates as the second target flow rate;

[0145] The first temperature is obtained according to the hot air valve opening, the ambient temperature, the first target flow rate and the second target flow rate.

[0146] In some possible embodiments, obtaining the first temperature according to the hot air valve opening, the ambient temperature, the first target flow rate, and the second target flow rate includes:

[0147] The hot air valve flow corresponding to the hot air valve opening is searched in a preset opening-flow database; wherein the preset opening-flow database includes at least two standard valve openings and a standard valve flow corresponding to each standard valve opening;

[0148] The hot air valve flow, ambient temperature, first target flow and second target flow are normalized respectively, and the normalized hot air valve flow, ambient temperature, first target flow and second target flow are input into the first deep learning model to obtain the first temperature; wherein, the first deep learning model is trained by at least two groups of standard valve flows and standard temperature sets corresponding to each group of standard valve flows, each group of standard valve flows includes standard hot air flow, standard steam flow and standard water injection flow, and each group of standard temperature sets includes standard ambient temperature and standard processing temperature.

[0149] In some possible embodiments, determining the second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment includes:

[0150] When it is detected that the difference between the temperature of the feed inlet and the temperature of the discharge outlet of the tobacco processing equipment is within a preset third interval, a weighted summation process is performed on the temperature of the feed inlet and the temperature of the discharge outlet according to a preset weight to obtain a second temperature;

[0151] When it is detected that the difference between the temperature of the feed port and the temperature of the discharge port of the tobacco processing equipment is not within the preset third interval, a temperature warning signal is sent to the user terminal.

[0152] In some possible embodiments, after setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes:

[0153] Acquire an image of tobacco leaves output from a discharge port of tobacco leaf processing equipment, and perform standardization processing on the image;

[0154] Extracting tobacco leaf texture features from the standardized image and inputting the tobacco leaf texture features into a second deep learning model to obtain the moisture content of the tobacco leaf; wherein the second deep learning model is trained using at least two standard texture features and a standard moisture content corresponding to each standard texture feature;

[0155] When it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, a valve adjustment signal is sent to the tobacco leaf processing equipment, so that the tobacco leaf processing equipment adjusts the steam valve opening and the water injection valve opening respectively.

[0156] In some possible embodiments, after setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes:

[0157] When it is detected that the discharge port temperature does not exceed the preset temperature threshold, the target valve opening is calculated according to the difference between the discharge port temperature and the preset temperature threshold;

[0158] The target valve opening is sent to the tobacco processing equipment so that the tobacco processing equipment controls the opening of the hot air valve to be consistent with the target valve opening.

[0159] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above method. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive, a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0160] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0161] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0162] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0163] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0164] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

Claims

1. A temperature detection method for tobacco processing equipment, characterized in that: include: When the tobacco processing equipment is in operation, obtaining at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals; Determining a target time according to all the steam flow rates and all the water injection flow rates, and obtaining a hot air valve opening and an ambient temperature of the tobacco processing equipment based on the target time; Obtaining a first temperature based on the hot air valve opening, the ambient temperature, all the steam flow rates, and all the water injection flow rates, and determining a second temperature based on the inlet temperature and the outlet temperature of the tobacco processing equipment; When it is detected that the difference between the first temperature and the second temperature is within a preset first interval, the first temperature is used as the processing temperature of the tobacco processing equipment; Wherein, determining the target time according to all the steam flow rates and all the water injection flow rates includes: Dividing all the steam flow rates into at least two first flow rate sets, and calculating a first difference between any two steam flow rates in each of the first flow rate sets; wherein each of the first flow rate sets includes the steam flow rates at three adjacent collection moments; When it is detected that all the first differences corresponding to any one of the first flow sets are within a preset second interval, the maximum acquisition time in the corresponding first flow set is used as the starting time, and all water injection flows are eliminated based on the starting time; Dividing all the water injection flows after the elimination process into at least two second flow sets, and calculating a second difference between any two water injection flows in each second flow set; wherein each second flow set includes the water injection flows at three adjacent collection moments; When it is detected that all the second differences corresponding to any one of the second flow sets are within the preset second interval, the maximum collection time in the corresponding second flow set is used as the target time; The obtaining of the first temperature according to the hot air valve opening, the ambient temperature, all the steam flows, and all the water injection flows comprises: screening out the steam flow rate corresponding to the starting moment and at least one adjacent steam flow rate from all the steam flow rates, and taking an average value of all the screened steam flow rates as a first target flow rate; Screening out the water injection flow rate corresponding to the target time and at least one adjacent water injection flow rate from all the water injection flow rates, and taking the average result of all the screened water injection flow rates as the second target flow rate; A first temperature is obtained according to the hot air valve opening, the ambient temperature, the first target flow rate, and the second target flow rate; the first temperature is obtained based on the hot air valve flow rate corresponding to the hot air valve opening, the ambient temperature, the first target flow rate, the second target flow rate, and a first deep learning model; The determining the second temperature based on the feed inlet temperature and the discharge outlet temperature of the tobacco processing equipment includes: When it is detected that the difference between the feed inlet temperature and the discharge outlet temperature of the tobacco processing equipment is within a preset third interval, a weighted summation process is performed on the feed inlet temperature and the discharge outlet temperature according to a preset weight to obtain a second temperature; When it is detected that the difference between the temperature of the feed port and the temperature of the discharge port of the tobacco processing equipment is not within the preset third interval, a temperature warning signal is sent to the user terminal.

2. The method according to claim 1, characterized in that The obtaining of the first temperature according to the hot air valve opening, the ambient temperature, the first target flow rate, and the second target flow rate includes: Querying a preset opening-flow rate database for the hot air valve flow rate corresponding to the hot air valve opening; wherein the preset opening-flow rate database includes at least two standard valve openings and a standard valve flow rate corresponding to each of the standard valve openings; The hot air valve flow, the ambient temperature, the first target flow and the second target flow are normalized respectively, and the normalized hot air valve flow, the ambient temperature, the first target flow and the second target flow are input into a first deep learning model to obtain a first temperature; wherein, the first deep learning model is trained by at least two groups of standard valve flows and a standard temperature set corresponding to each group of the standard valve flows, each group of the standard valve flows includes a standard hot air flow, a standard steam flow and a standard water injection flow, and each group of the standard temperature set includes a standard ambient temperature and a standard processing temperature.

3. The method according to claim 1, characterized in that After setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes: Acquiring an image of tobacco leaves output from a discharge port of the tobacco leaf processing equipment, and performing standardization processing on the image; Extracting tobacco leaf texture features from the standardized image, and inputting the tobacco leaf texture features into a second deep learning model to obtain the moisture content of the tobacco leaf; wherein the second deep learning model is trained using at least two standard texture features and a standard moisture content corresponding to each of the standard texture features; When it is detected that the moisture content of the tobacco leaves is not within the preset moisture content range, a valve adjustment signal is sent to the tobacco leaf processing equipment, so that the tobacco leaf processing equipment adjusts the steam valve opening and the water injection valve opening respectively.

4. The method according to claim 1, wherein After setting the first temperature as the processing temperature of the tobacco leaf processing equipment, the method further includes: When it is detected that the temperature of the discharge port does not exceed the preset temperature threshold, the target valve opening is calculated according to the difference between the temperature of the discharge port and the preset temperature threshold; The target valve opening is sent to the tobacco processing equipment so that the tobacco processing equipment controls the opening of the hot air valve to be consistent with the target valve opening.

5. A temperature detection system for tobacco processing equipment, characterized in that: The system is applied to the temperature detection method for tobacco processing equipment according to any one of claims 1 to 4, and the system comprises: A first acquisition module is configured to acquire at least two steam flow rates and at least two water injection flow rates of the tobacco processing equipment at preset time intervals when the tobacco processing equipment is in operation; a second acquisition module, configured to determine a target time according to all the steam flow rates and all the water injection flow rates, and acquire the hot air valve opening and the ambient temperature of the tobacco processing equipment based on the target time; a third acquisition module, configured to obtain a first temperature based on the hot air valve opening, the ambient temperature, all the steam flow rates, and all the water injection flow rates, and determine a second temperature based on the feed inlet temperature and the discharge outlet temperature of the tobacco processing equipment; The temperature determination module is used to use the first temperature as the processing temperature of the tobacco processing equipment when it is detected that the difference between the first temperature and the second temperature is in a preset first interval.

6. A temperature detection system for tobacco processing equipment, characterized in that: including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes the steps of the method according to any one of claims 1 to 4.

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