An automatic detection and control device for color change of materials in a baking machine

Abstract

This utility model belongs to the field of tobacco machinery technology, specifically relating to an automatic detection and control device for color changes of materials in a tobacco curing machine. The device includes a tobacco curing machine, an analysis system, a control system, and a camera. This application achieves precise image acquisition and comparison of the material's state before and after curing by installing cameras at the inlet and outlet of the curing machine and combining them with RFID card positioning technology. Utilizing an intelligent analysis system to process and analyze the images in real time, the degree of color change in the tobacco leaves can be accurately calculated, and the maturity of the tobacco leaves can be predicted through advanced data analysis models. This provides a scientific and reliable basis for precise control of the curing process, avoiding the subjectivity and uncertainty of traditional manual judgment.

Description

Technical Field

[0001] This utility model belongs to the field of tobacco machinery technology, specifically relating to an automatic detection and control device for color changes of materials in a roasting machine. Background Technology

[0002] In tobacco curing, the color of tobacco leaves is a crucial indicator of their quality. Traditional tobacco leaf (stem) curing machines lack precise, real-time monitoring methods for color changes during the curing process, often relying on manual experience to judge the degree of curing and adjust curing parameters. This makes precise control of the curing process difficult, easily leading to problems such as scorching and overly reddish tobacco, severely affecting the uniformity of color and the stability of flavor, resulting in significant fluctuations in product quality and reduced market competitiveness. Furthermore, traditional curing methods cannot accurately predict the maturity of tobacco leaves, making it difficult to complete curing at the optimal time, further impacting the quality of the tobacco leaves. Therefore, developing a device capable of real-time, precise monitoring of tobacco leaf color changes and automatic control of the curing process is of significant practical importance.

[0003] This application is submitted in order to address the above issues. Utility Model Content

[0004] This application aims to solve problems such as inaccurate color monitoring, untimely adjustment of roasting parameters, and unstable product quality in the existing tobacco leaf and stem roasting process.

[0005] This application provides an automatic detection and control device for color change of materials in a tobacco curing machine, the device comprising: a tobacco curing machine 1, an analysis system, and a control system;

[0006] Multiple entrance cameras 3 are arranged around the entrance 1-1 of the tobacco curing machine 1. The entrance cameras 3 are configured to capture images of the initial state of the material entering the tobacco curing machine 1.

[0007] Multiple outlet cameras 5 are provided around the outlet 1-2 of the tobacco curing machine 1. The outlet cameras 5 are configured to capture images of the material discharged from the tobacco curing machine 1.

[0008] Multiple radio frequency identification cards 2 are installed on the material conveyor belt inside the tobacco curing machine 1, and the multiple radio frequency identification cards 2 are configured as follows:

[0009] As the material conveyor belt of the tobacco curing machine 1 moves synchronously, and when the material enters the shooting area of ​​the tobacco curing machine inlet 1-1, the corresponding inlet camera 3 is triggered to shoot and record the initial state image of a piece of material before curing, and the information of the radio frequency identification card 2 is associated with the image data;

[0010] When the material reaches the tobacco curing machine outlet 1-2, the outlet camera 5 is triggered again to capture the post-curing image based on the information from the RFID card 2.

[0011] The analysis system is configured to: analyze images of the same piece of material before and after baking corresponding to the same RFID card 2 and calculate the degree of color change of the material to predict the maturity of the material;

[0012] The control system is configured to dynamically adjust the curing temperature and time of the tobacco curing machine 1 based on the calculation results of the analysis system.

[0013] Preferably, the plurality of RFID cards 2 are distributed at intervals along the direction of movement of the material conveyor belt.

[0014] The materials mentioned above are tobacco stems or leaves. The analysis system is an intelligent analysis system.

[0015] Preferably, the device further includes a human-machine interface, which facilitates the operator's monitoring and operation of the device.

[0016] Preferably, the analysis system is configured to: calculate the degree of color change of the entire batch of materials by analyzing images of multiple pieces of materials before and after baking, and predict the maturity of the entire batch of materials.

[0017] Compared with the prior art, this application has the following advantages:

[0018] 1. Precise Color Monitoring and Maturity Prediction: By installing high-resolution CCD cameras at the inlet and outlet of the tobacco curing machine, and combining this with RFID card (Radio Frequency Identification) positioning technology, precise image acquisition and comparison of the tobacco leaves (stems) before and after curing are achieved. Using an intelligent analysis system to process and analyze the images in real time, the degree of color change in the tobacco leaves can be accurately calculated. Furthermore, advanced data analysis models can predict the maturity of the tobacco leaves, providing a scientific and reliable basis for precise control of the curing process and avoiding the subjectivity and uncertainty of traditional manual judgment.

[0019] 2. Optimizing the roasting process and improving product quality: The control system dynamically adjusts the roasting temperature and time based on the results of the intelligent analysis system, ensuring that the tobacco leaves are processed under optimal roasting conditions. This effectively reduces problems such as scorching and reddish tobacco, improves the uniformity of tobacco leaf color and the stability of taste, making the product quality more stable and reliable, and significantly enhancing the product's market competitiveness. At the same time, precise roasting control also helps to improve the utilization rate of tobacco leaves, reduce production costs, and improve the company's economic benefits.

[0020] 3. Strong self-learning and adaptability: The self-learning function of the intelligent analysis system enables it to automatically adjust the color feature extraction parameters and maturity judgment standards according to the characteristics of tobacco leaves of different varieties and origins, adapting to diverse production needs. It eliminates the need for frequent manual adjustment of device parameters, improving production efficiency and the level of intelligence of the device, and providing tobacco processing enterprises with a more flexible and efficient production solution.

[0021] 4. Excellent ease of operation and reliability: Preferably, this application also designs a human-machine interface, facilitating operators' monitoring and operation of the device. This allows them to intuitively understand the curing process of the tobacco leaves and the operating status of the device, and to intervene manually when necessary, improving the controllability of the production process and the ease of operation. Simultaneously, the entire device adopts a dustproof, waterproof, and high-temperature resistant design, and the outer shells of each component are made of high-quality materials, enabling it to withstand the harsh working environment inside the curing machine. This ensures long-term stable operation of the device, reduces equipment failure rate, improves equipment reliability and service life, reduces equipment maintenance costs and downtime, and guarantees the continuity and stability of production. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the automatic detection and control device for material color change in the baking machine of this application.

[0023] List of reference numerals in the attached diagram:

[0024] 1. Tobacco curing machine; 1-1. Tobacco curing machine inlet; 1-2. Tobacco curing machine outlet; 2. Radio frequency identification card; 3. Inlet camera; 4. Material movement direction; 5. Outlet camera. Detailed Implementation

[0025] The present application will now be described in further detail with reference to the embodiments.

[0026] Those skilled in the art will understand that the following embodiments are for illustrative purposes only and should not be construed as limiting the scope of this application. Where specific techniques or conditions are not specified in the embodiments, they are performed in accordance with the techniques or conditions described in the literature in the field or according to the product manual. Materials or equipment whose manufacturers are not specified are all conventional products that can be obtained by purchase.

[0027] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. In the description of this application, unless otherwise stated, “a plurality” means two or more. It should be further understood that the term “comprising” as used in the specification of this application means the presence of the stated feature, integer, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” to another element, it can be directly connected to the other element, or there may be an intermediate element. Furthermore, the term “connected” as used herein can include wireless connections.

[0028] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0029] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0030] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0031] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0032] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. The illustrative expressions of the above terms in this specification should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0033] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0034] The purpose of this application is to provide an automatic detection and control device for slight color changes in tobacco leaves (stems) during the curing process. By adopting advanced image acquisition and analysis technology and intelligent control algorithms, the device can achieve real-time monitoring and precise analysis of color changes during the curing process of tobacco leaves (stems), automatically adjust the curing temperature and time, improve the uniformity of tobacco leaf color and the stability of taste, reduce quality fluctuations, optimize the curing process, and enhance the market competitiveness of the product.

[0035] The automatic detection and control device for slight color change of tobacco leaves (stems) roasting machine in this application mainly includes the following key components and structural designs:

[0036] I. Image Acquisition System:

[0037] 1. Three CCD high-definition cameras (left, center, and right) are horizontally arranged at the inlet 1-1 of the tobacco curing machine as inlet cameras 2, used to capture initial images of the tobacco leaves (stems) entering the curing machine. The CCD high-definition cameras have high resolution, high sensitivity, and excellent color reproduction capabilities, enabling them to clearly and accurately capture details such as the color and texture of the tobacco leaves, providing high-quality image data for subsequent color analysis.

[0038] 2. Three CCD high-definition cameras (left, center, and right) are also installed horizontally at the outlets 1-2 of the tobacco curing machine as outlet cameras 5 to capture images of the cured tobacco leaves (stems). The installation positions and angles of these cameras are precisely adjusted to ensure comprehensive and seamless coverage of the material areas at the inlet and outlet of the curing machine, guaranteeing the representativeness and accuracy of the collected images.

[0039] Of course, the camera can be installed in other locations, as long as it can fully and without blind spots cover the material area at the entrance and exit of the baking machine, ensuring that the collected images are representative and accurate.

[0040] 3. Multiple RFID cards are installed on the main mesh belt chain drive of the tobacco curing machine 1. Each RFID card has a unique identification code corresponding to a specific location of tobacco flakes (stems). Through the RFID card positioning system, when the material enters the shooting area at the inlet of the curing machine, the corresponding CCD high-definition camera is triggered to capture an image of the material's initial state, and the RFID card information is linked to the image data. When the material reaches the outlet of the curing machine, the camera at the outlet is triggered again based on the RFID card information to capture a post-curing image, thus achieving accurate comparison of the tobacco flakes (stems) before and after curing, providing a reliable data basis for color change analysis. The RFID card is also known as the radio frequency identification card 2.

[0041] II. Intelligent Analysis and Control System:

[0042] 1. The intelligent analysis system connected to the CCD high-definition camera employs advanced image processing algorithms and color analysis models to process and analyze the acquired pre- and post-baking images in real time. First, the images undergo preprocessing, including grayscale conversion, filtering, and enhancement, to remove noise interference and improve image clarity and contrast. Then, using color space conversion technology, the image is converted from the RGB color space to the HSV (Hue, Saturation, Brightness) color space, allowing for more accurate extraction of the tobacco leaf's color characteristic parameters, such as hue, saturation, and brightness values.

[0043] 2. The intelligent analysis system, based on preset color standards and empirical data, combined with real-time extracted color feature parameters, uses intelligent algorithms to calculate the degree of color change in tobacco leaves and predicts the maturity of the leaves through a data analysis model. This intelligent algorithm can employ machine learning algorithms, such as neural network algorithms or support vector machine algorithms. After training with a large amount of sample data, it can accurately determine the curing status and maturity of tobacco leaves based on color changes, providing a scientific basis for adjusting curing parameters.

[0044] 3. The control system dynamically adjusts the roasting temperature and time of the roaster based on the calculation results of the intelligent analysis system. When it detects that the color change of the tobacco leaves is slow and has not yet reached the expected maturity, the control system automatically increases the roasting temperature by ±1℃ each time and appropriately extends the roasting time by 2 minutes each time to accelerate the roasting process. Conversely, when the color change of the tobacco leaves is too fast and they are close to being charred, the control system quickly lowers the roasting temperature, reduces heat input, and shortens the roasting time to ensure that the tobacco leaves are roasted at the best color and taste, achieving precise control of the roasting process.

[0045] One specific structure of the automatic detection and control device for material color change in the baking machine in this application is as follows: Figure 1 As shown. The device includes:

[0046] Three CCD high-definition cameras, arranged horizontally at the inlet of the oven and three CCD high-definition cameras, arranged horizontally at the outlet of the oven, are used to collect images of tobacco leaves (stems) before and after baking.

[0047] Multiple RFID cards and a corresponding positioning system are installed on the main mesh belt chain drive of the roasting machine. The RFID cards enable precise positioning and photography of the tobacco sheet (stem) material before and after roasting.

[0048] The intelligent analysis system connected to a CCD high-definition camera uses image processing algorithms and color analysis models to analyze the acquired images in real time, calculate the degree of color change of tobacco leaves, and predict maturity.

[0049] The control system dynamically adjusts the baking temperature and time of the oven based on the results of the intelligent analysis system.

[0050] The device monitors and automatically controls the color changes of tobacco leaves (stems) in real time during the curing process, ensuring the precision of the curing process, improving the uniformity of tobacco leaf color and the stability of taste, reducing quality fluctuations, enhancing product market competitiveness, and optimizing the tobacco curing process.

[0051] Preferably, the lens of the CCD high-definition camera adopts optical image stabilization technology to ensure that clear and stable images can be captured under stress test vibration environment, thereby improving the accuracy and reliability of image acquisition.

[0052] Preferably, the RFID card has a reading distance of 1-20 cm and an identification accuracy of no less than 99.9%, which can quickly and accurately locate tobacco leaves (stems) materials, ensure accurate comparison of images before and after baking, and provide reliable data support for color change analysis.

[0053] Preferably, the image processing algorithm and color analysis model of the intelligent analysis system have self-learning capabilities, which can automatically adjust the color feature extraction parameters and maturity judgment criteria according to the characteristics of tobacco leaves of different varieties and origins, thereby improving the adaptability and analysis accuracy of the device to different tobacco leaves and meeting diverse production needs.

[0054] Preferably, the temperature adjustment accuracy of the control system is ±1℃, and the time adjustment accuracy is ±2 minutes. It can quickly and accurately adjust the roasting parameters of the roaster according to the instructions of the intelligent analysis system, ensuring that the tobacco leaves are processed under the best roasting conditions, thereby improving product quality and production efficiency.

[0055] Preferably, the device also includes a human-machine interface, through which operators can view data on the color change of tobacco leaves, records of roasting parameter adjustments, and operating status information of the device. They can also manually input some special process parameters or intervene in the operation of the control system. The human-machine interface is simple to operate, intuitive and easy to understand, which improves the ease of operation of the device and the controllability of the production process.

[0056] Preferably, the overall structure of the device adopts a dustproof, waterproof, and high-temperature resistant design, and the outer shell of each component is made of stainless steel or other high-temperature and corrosion-resistant materials, which can adapt to the harsh working environment of high temperature, high humidity, and dust inside the oven, ensuring long-term stable operation of the device, reducing equipment failure rate, and improving equipment reliability and service life.

[0057] The following are the specific implementation steps of the automatic detection and control device for slight color change in tobacco sheet (stem) roasting machine in this application:

[0058] I. Equipment Installation and Commissioning:

[0059] 1. Install three CCD high-definition cameras (left, center, and right) horizontally at the inlet and outlet of the tobacco curing machine according to design requirements. Adjust the installation angle and position of the cameras to ensure they can clearly and comprehensively capture the tobacco sheet (stem) material at the inlet and outlet of the curing machine. Connect the power and signal cables of the cameras to the intelligent analysis system for initial image acquisition debugging. Check whether the cameras are working properly, whether the captured images are clear and accurate, and whether the image transmission is stable and uninterrupted.

[0060] 2. Evenly install multiple RFID cards on the main mesh belt chain drive of the baking machine, ensuring that each RFID card is securely installed without loosening or falling off. Install the RFID card reader and connect it to the positioning system to conduct RFID card identification and positioning tests. Check whether the reader can accurately and quickly read the RFID card information, and whether the positioning system can accurately trigger the corresponding CCD high-definition camera to take pictures based on the RFID card information, ensuring accurate acquisition and comparison of images before and after baking.

[0061] 3. Install the intelligent analysis system and control system, connect the communication lines and data cables between all components, connect the intelligent analysis system to the CCD high-definition camera and control system, and connect the control system to the heating and transmission systems of the oven to establish a stable signal transmission and control channel. Initialize the intelligent analysis system by importing preset color standards, image processing algorithms, and color analysis model parameters. Perform preliminary system debugging to check whether the intelligent analysis system can accurately receive image data collected by the camera and perform effective image processing and color analysis to calculate the correct degree of color change and maturity prediction results. Simultaneously, check whether the control system can accurately adjust the oven's baking temperature and time according to the instructions of the intelligent analysis system.

[0062] 4. Install the human-machine interface and connect it to the intelligent analysis and control systems. Conduct operational tests on the interface to check whether operators can easily view data on tobacco leaf color changes, curing parameter adjustment records, and equipment operating status information through the interface, and whether they can manually input special process parameters or intervene in the control system's operation. Optimize the display content and operation flow of the human-machine interface to improve its ease of use and intuitiveness.

[0063] 5. Conduct a comprehensive inspection of the entire device to ensure that all components are installed correctly, that there are no loose connections or short circuits, and that communication between systems is normal. Perform a no-load test run to check the image acquisition system's shooting effect, the intelligent analysis system's analysis results, the control system's adjustment functions, and the human-machine interface's display and operation functions to ensure they are normal. Address and optimize any problems discovered during the test run promptly.

[0064] II. Operations during the production process:

[0065] 1. During the tobacco leaf (stem) curing process, the material enters the curing machine via the main mesh belt chain drive. When material with an RFID card enters the imaging area at the inlet of the curing machine, the RFID card positioning system triggers the CCD high-definition camera at the inlet to capture an image of the material before curing. The image data is then linked to the RFID card information and transmitted to the intelligent analysis system. The intelligent analysis system preprocesses and performs color analysis on the pre-curing image, extracting initial color characteristic parameters of the tobacco leaves, such as hue, saturation, and brightness values. This data is stored in a database as the basis for subsequent color change analysis.

[0066] 2. During the roasting process inside the roaster, the control system controls the heating and transmission systems of the roaster according to preset roasting process parameters, ensuring that the tobacco leaves are roasted according to the predetermined temperature curve and time schedule. Simultaneously, the intelligent analysis system continuously monitors the roaster's operating status and time, and prepares to receive post-roasting images captured by the CCD high-definition camera at the outlet when the material approaches the roaster's outlet.

[0067] 3. When the material reaches the shooting area at the exit of the roasting machine, the RFID card positioning system triggers the CCD high-definition camera at the exit to photograph the roasted material again and transmits the roasted image data to the intelligent analysis system. The intelligent analysis system performs the same preprocessing and color analysis on the roasted image, extracts the color feature parameters of the roasted tobacco leaves, compares them with the color feature parameters before roasting, and calculates the degree of color change and maturity prediction results of the tobacco leaves.

[0068] 4. Based on the calculation results of the intelligent analysis system, the control system determines whether the curing state of the tobacco leaves meets expectations. If the color of the tobacco leaves changes slowly and has not yet reached the expected maturity, the control system automatically increases the curing temperature, for example, by increasing the temperature by [X]℃ and appropriately extending the curing time by [X] minutes, and then continues to monitor the color change of the tobacco leaves; conversely, if the color of the tobacco leaves changes too quickly and is close to charred, the control system quickly reduces the curing temperature, such as by decreasing it by [X]℃, and shortens the curing time by [X] minutes to ensure that the tobacco leaves are cured in the best color and taste condition.

[0069] 5. Throughout the roasting process, operators can view real-time data on the color changes of the tobacco leaves, roasting parameter adjustment records, and the operating status of the equipment through the human-machine interface. If any abnormalities are detected or special adjustments to the roasting process are required based on actual production conditions, operators can manually input relevant process parameters or intervene in the control system to ensure smooth production and stable product quality.

[0070] III. Equipment Maintenance and Care:

[0071] 1. Regularly clean the lens surface of the CCD high-definition camera to prevent dust, tar, and other impurities from affecting the shooting effect. Check whether the camera's mounting bracket and connecting cables are secure; tighten them promptly if they are loose. Regularly calibrate and adjust the camera, checking whether its resolution, color reproduction, and other performance indicators meet the requirements; repair or replace it promptly if any degradation occurs.

[0072] 2. Regularly check the installation of RFID cards and the working status of the reading device to ensure that the RFID cards are undamaged and unlost, and that the reading device can accurately and quickly read the card information. Perform regular cleaning and maintenance on the RFID cards to prevent dust and debris from affecting their recognition accuracy. If any malfunction is found in the RFID card or reading device, replace or repair it promptly to ensure accurate positioning and acquisition of images before and after baking.

[0073] 3. Regularly maintain the computer hardware of the intelligent analysis system, including cleaning up hard drive junk files, updating the operating system and antivirus software, and checking the operating status of hardware devices (such as hard drives, memory, and graphics cards) to ensure that the computer has sufficient computing power and storage space to process large amounts of image data and perform complex color analysis calculations. Regularly back up important data and model parameters of the intelligent analysis system to prevent data loss. Simultaneously, regularly upgrade and optimize the software of the intelligent analysis system, adjusting image processing algorithms and color analysis models according to new tobacco varieties and curing process requirements to improve the system's analytical accuracy and adaptability.

[0074] 4. Regularly inspect and maintain the controller, drivers, sensors, and other components of the control system. Check if the controller program is running normally, for any error codes or crashes, and regularly upgrade and optimize the controller program to improve its control performance and stability. Check the operating status of the drivers, including the motor's operating sound, temperature, vibration, etc., and regularly add lubricating oil and replace worn parts. Calibrate the measurement accuracy of the sensors to ensure they can accurately collect operating parameters such as temperature and time of the oven, and replace damaged sensors promptly.

[0075] 5. Regularly inspect the hardware of the human-machine interface, such as the display screen, buttons, and controllers. Clean the surfaces of dust and debris to prevent button malfunction or display abnormalities caused by dust accumulation. Check the communication lines between the human-machine interface and the intelligent analysis and control systems. If any are loose or damaged, repair them promptly to ensure that operators can operate and monitor the device normally through the interface.

[0076] 6. Conduct regular inspections of the overall structure of the device, including whether the outer casing of each component is damaged or deformed, and whether the waterproof, dustproof, and high-temperature resistant seals are intact. If any problems are found, repair or replace them in a timely manner to ensure that the device can adapt to the harsh working environment inside the oven, operate stably for a long time, reduce the equipment failure rate, and improve the reliability and service life of the equipment.

[0077] Through the above specific implementation methods, the automatic detection and control device for micro-color change of tobacco leaves (stems) in this application can effectively realize real-time monitoring and automatic control of color changes during the tobacco leaf (stem) roasting process, thereby improving the roasting quality of tobacco leaves and the market competitiveness of the products.

Claims

1. An automatic detection and control device for color change of materials in a baking machine, characterized in that, The device includes: a tobacco curing machine (1), an analysis system, and a control system; Multiple entrance cameras (3) are provided around the entrance (1-1) of the tobacco curing machine (1). The entrance cameras (3) are configured to capture images of the initial state of the material entering the tobacco curing machine (1). Multiple outlet cameras (5) are provided around the outlet (1-2) of the tobacco curing machine (1). The outlet cameras (5) are configured to capture images of the material discharged from the tobacco curing machine (1). Multiple radio frequency identification cards (2) are installed on the material conveyor belt inside the tobacco curing machine (1), and the multiple radio frequency identification cards (2) are configured as follows: As the material conveyor belt of the tobacco curing machine (1) moves synchronously, and when the material enters the shooting area of ​​the tobacco curing machine inlet (1-1), the corresponding inlet camera (3) is triggered to shoot and record the initial state image of a piece of material before curing, and the information of the radio frequency identification card (2) is associated with the image data. When the material reaches the outlet (1-2) of the tobacco curing machine, the outlet camera (5) is triggered again to take a picture of the cured tobacco based on the information of the radio frequency identification card (2); The analysis system is configured to: analyze the images of the same piece of material before and after baking corresponding to the same radio frequency identification card (2) and calculate the degree of color change of the material to predict the maturity of the material; The control system is configured to adjust the curing temperature and time of the tobacco curing machine (1) based on the calculation results of the analysis system.

2. The automatic detection and control device for material color change in the baking machine according to claim 1, characterized in that, The plurality of RFID cards (2) are spaced apart along the direction of movement of the material conveyor belt.

3. The automatic detection and control device for material color change in the oven according to claim 1, characterized in that, The analysis system is configured to: calculate the degree of color change of the entire batch of materials by analyzing images of multiple pieces of material before and after baking, and predict the maturity of the entire batch of materials.

Images