A kind of threshing and redrying online monitoring method and device

Abstract

This invention discloses an online monitoring method and device for tobacco leaf threshing and re-drying. The method includes: acquiring images of tobacco leaves at various workstations; converting the acquired analog image signals into digital signals; transmitting the digital signals; processing the image data and determining the tobacco leaf status; and outputting control and warning signals based on the determined tobacco leaf status. The tobacco leaf status includes the presence or absence of material, the height of the material, the movement of the material, and the material fluctuation coefficient. The purpose of this invention is to provide an online monitoring method and device for tobacco leaf threshing and re-drying to monitor the threshing and re-drying process, enabling timely alarms to be issued when problems such as blockage, material stoppage, material interruption, and large flow fluctuations occur, allowing staff to quickly handle the situation and thus ensuring the continuity and stability of production.

Description

Technical Field

[0001] This invention relates to the field of detection technology, specifically to an online monitoring method and device for leaf re-drying. Background Technology

[0002] In the crucial production process of leaf re-drying, the transportation of materials on the conveyor belt and their condition in related equipment such as leaf storage cabinets and vibrating screens are of paramount importance to the continuity and stability of the entire production process.

[0003] Traditional material monitoring methods largely rely on manual inspections. Specifically, inspectors need to periodically check various areas of equipment such as conveyor belts, leaf storage cabinets, and vibrating screens. This method has many drawbacks. It is extremely inefficient because inspectors can only check a limited area at a time, and covering all equipment requires a significant amount of time. Furthermore, this method is labor-intensive; inspectors are prone to fatigue from prolonged work, which can lead to oversights. More importantly, manual inspections struggle to achieve real-time and accurate monitoring of material conditions. For example, when material becomes blocked, it may initially be a minor, localized blockage. Without timely monitoring, this blockage may not be detected immediately, eventually developing into a complete material stoppage. Similarly, material shortages, if not detected promptly, will force production to halt. Such material condition issues cannot be detected in time through manual inspections, leading to production interruptions, inconsistent product quality, and severe impacts on the entire production process.

[0004] As the tobacco industry continues to develop, the demands for intelligent and automated production processes are also constantly increasing. In this context, the entire industry urgently needs a device capable of precise online monitoring of key process points in the tobacco leaf re-drying production line. This monitoring must not only accurately track the status of materials in each piece of equipment in real time, but also promptly issue alarms when problems such as blockages, material stoppages, material shortages, and large flow fluctuations occur, allowing staff to quickly address the issues. This ensures the continuity and stability of production, improves product quality, and avoids resource waste. Summary of the Invention

[0005] The purpose of this invention is to provide an online monitoring method and device for leaf re-drying, so as to monitor the leaf re-drying process and issue timely alarms when problems such as blockage, material stoppage, material interruption and large flow fluctuation occur, so that staff can deal with them quickly, thereby ensuring the continuity and stability of production.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A method for online monitoring of leaf re-baking includes:

[0008] Collect images of tobacco leaves at each workstation;

[0009] The acquired analog image signals are converted into digital signals;

[0010] To transmit digital signals;

[0011] The image data is processed and the tobacco leaf status is determined. Based on the determined tobacco leaf status, control signals and warning signals are output. The tobacco leaf status includes the presence or absence of material, the height of material, the movement of material, and the fluctuation coefficient of material.

[0012] Furthermore, in the process of processing the image data and determining the state of the tobacco leaves, when determining whether the material is present, the acquired image is first converted to grayscale, and then an appropriate grayscale threshold is set to distinguish the material from the background. When the grayscale threshold is reached, it is determined that the material is present.

[0013] Furthermore, the image data processing and tobacco leaf condition determination involves image segmentation technology to segment the material area from the image when determining the material height. Then, by calculating the number of pixels or area of ​​the material area, and combining this with known storage cabinet dimensions and camera shooting angle, focal length, and other parameters, the actual height of the material is calculated using geometric relationships. The height formula is as follows:

[0014]

[0015] In this formula, This refers to the actual height of the leaf storage cabinet. Determine the installation height of the camera. The pixel height of the material in the image, α represents the vertical pixel resolution of the image, and α represents the vertical viewing angle of the camera.

[0016] Furthermore, the image data is processed to determine the state of the tobacco leaves. The movement of the material is assessed using a frame difference method, which processes consecutive image frames to calculate the positional change of the material between adjacent frames. By setting a displacement threshold, when the displacement of the material between two frames exceeds this threshold, the material is determined to be in a moving state; otherwise, it is determined to be stationary. The formula for its movement speed is as follows:

[0017] In this formula, The time interval between two adjacent frames. This represents the number of pixels the material has shifted in the image. The horizontal pixel resolution of the image, and the horizontal field of view of the β camera. This represents the actual speed at which the material moves.

[0018] Furthermore, in the process of processing the image data and determining the state of the tobacco leaves, the formula for the material fluctuation coefficient is as follows:

[0019]

[0020] In this formula, Let Q1 be the flow rate fluctuation coefficient, Q2 be the flow rate at time t1, and Q2 be the flow rate at time t2. It is the time interval between two adjacent frames, i.e., the difference between t1 and t2;

[0021] when When the threshold is exceeded, it is determined to be an abnormal flow fluctuation.

[0022] Furthermore, in the process of processing image data and determining the state of tobacco leaves, when determining the clogging status of the vibrating screen mesh, texture analysis is performed on the image of the vibrating screen material. By extracting the texture features of the image, the uniformity of the distribution of the vibrating screen material and the clogging status of the mesh are determined. The texture features of the image include the energy, contrast, and correlation of the gray-level co-occurrence matrix.

[0023] On the other hand, this application also provides an online monitoring device for leaf re-drying, including...

[0024] CCD high-definition cameras are used to capture images of tobacco leaves at each workstation;

[0025] An image acquisition card is used to convert acquired analog image signals into digital signals.

[0026] A wireless communication module is used to transmit digital signals.

[0027] The industrial control system is configured to process image data and determine the status of tobacco leaves, and output control signals and warning signals based on the determined status of tobacco leaves;

[0028] Furthermore, the CCD high-definition cameras are respectively installed on the conveyor belt, the leaf storage cabinet, and the vibrating screen, and the industrial control system is electrically connected to the conveyor belt, the leaf storage cabinet, and the vibrating screen respectively.

[0029] Furthermore, it also includes an alarm device, which is electrically connected to the industrial control system.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] This application collects data on the tobacco leaves on equipment such as conveyor belts, storage cabinets, and vibrating screens. It analyzes the images to determine whether there are problems such as material stoppage, blockage, material interruption, or large flow fluctuations. The signals are then transmitted to each piece of equipment to execute stop or adjustment operations. This achieves real-time and accurate monitoring of the material and facilitates timely processing. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating the online monitoring method in an embodiment of the present invention.

[0033] Figure 2 This is a structural block diagram of the online monitoring device in an embodiment of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0035] refer to Figure 1 As shown, this application provides an online monitoring method for leaf re-baking, comprising:

[0036] S101: Collect images of tobacco leaves at each workstation;

[0037] In this embodiment, the workstations to be sampled are the conveyor belt, the leaf storage cabinet, and the vibrating screen;

[0038] S102: Convert the acquired analog image signal into a digital signal;

[0039] S103: Transmit digital signals;

[0040] S104: Processes image data and determines the tobacco leaf status. Based on the determined tobacco leaf status, outputs control and warning signals. The tobacco leaf status includes the presence or absence of material, material height, material movement, and material fluctuation coefficient. Control signals are output to control equipment at each workstation. For example, when no material is detected on the conveyor belt, subsequent process equipment is automatically stopped to avoid idling; when the material height in the leaf storage cabinet reaches the upper limit, the feeding equipment is stopped; when the vibrating screen mesh is blocked, the vibration frequency of the vibrating screen is automatically adjusted or the vibrating screen is stopped for cleaning.

[0041] In addition, appropriate warning signals will be issued based on the severity and duration of the material abnormality. Warning methods include audible and visual alarms, SMS notifications, etc., to ensure that operators can promptly detect problems and take appropriate measures.

[0042] More specifically, in S104, when determining whether material is present, the acquired image is first converted to grayscale, and then an appropriate grayscale threshold is set to distinguish the material from the background. When the grayscale threshold is reached, it is determined that material is present.

[0043] In practical applications, the background color of the collection area needs to have a significant color difference from the tobacco leaves in order to ensure that the material can be distinguished from the background.

[0044] When determining the height of the material, image segmentation technology is used to segment the material area from the image. Then, by calculating the number of pixels or the area of ​​the material area, and combining this with known information about the storage cabinet dimensions and parameters such as the camera's shooting angle and focal length, the actual height of the material is calculated using geometric relationships. The formula for the height is as follows:

[0045] In this formula, This refers to the actual height of the leaf storage cabinet. Determine the installation height of the camera. The pixel height of the material in the image, α represents the vertical pixel resolution of the image, and α represents the vertical viewing angle of the camera.

[0046] When determining the movement of materials, a frame difference method is used to process consecutive image frames and calculate the positional change of the material between adjacent frames. By setting a displacement threshold, when the displacement of the material between two frames exceeds the threshold, the material is determined to be in a moving state; otherwise, it is determined to be stationary. The formula for its movement speed is as follows:

[0047] In this formula, The time interval between two adjacent frames. This represents the number of pixels the material has shifted in the image. The horizontal pixel resolution of the image, and the horizontal field of view of the β camera. This represents the actual speed at which the material moves.

[0048] The formula used to determine the fluctuation coefficient of materials is as follows:

[0049]

[0050] In this formula, Let Q1 be the flow rate fluctuation coefficient, Q2 be the flow rate at time t1, and Q2 be the flow rate at time t2. It is the time interval between two adjacent frames, i.e., the difference between t1 and t2;

[0051] when When the threshold is exceeded, it is determined to be an abnormal flow fluctuation.

[0052] In practical applications, image acquisition areas are set up at specific locations on the conveyor belt. By analyzing images of the materials within these areas, the quantity or area of ​​material passing through per unit time can be calculated. Combined with parameters such as the conveyor belt's operating speed and width, the material flow rate can be estimated.

[0053] When determining the clogging status of the vibrating screen mesh, texture analysis is performed on the image of the vibrating screen material. By extracting the texture features of the image, the uniformity of the distribution of the vibrating screen material and the clogging status of the mesh are determined. The texture features of the image include the energy, contrast, and correlation of the gray-level co-occurrence matrix.

[0054] Furthermore, a fault prediction model can be established in S104, using historical monitoring data and machine learning algorithms to predict potential equipment failures. For example, by analyzing the frequency and trend of screen mesh blockage, the maintenance cycle of the vibrating screen can be predicted, allowing for advance scheduling of maintenance work and reducing equipment downtime.

[0055] When texture feature parameters exceed the normal range, the presence of screen mesh blockage is determined by combining material flow information and screen operating parameters. For example, if the energy value is too low, the contrast is too high, and the material flow rate is significantly reduced, it can be determined that the mesh is blocked.

[0056] On the other hand, based on the above embodiments, this application also provides an online monitoring device for leaf re-drying, comprising:

[0057] CCD high-definition camera 1, used to capture images of tobacco leaves at each workstation;

[0058] When selecting a CCD high-definition camera, a high-resolution, high-frame-rate CCD high-definition camera should be chosen. It should be installed above or to the side of key process points on the production line to ensure clear imaging of materials within equipment such as conveyor belts, leaf storage cabinets, and vibrating screens. The camera should have automatic focusing and automatic dimming functions to adapt to different lighting conditions and changes in material height.

[0059] In practical applications, the CCD high-definition camera 1 is respectively installed on the conveyor belt, the leaf storage cabinet and the vibrating screen, and the industrial control system 4 is electrically connected to the conveyor belt, the leaf storage cabinet and the vibrating screen to control the shutdown or speed and frequency of each device.

[0060] Image acquisition card 2 is used to convert the acquired analog image signals into digital signals;

[0061] Wireless communication module 3 is used to transmit digital signals;

[0062] In the selection of wireless communication module 3, a GSM wireless communication module is adopted to establish a stable wireless connection with industrial control system 4. This module supports high-speed data transmission, ensuring that real-time monitoring data can be uploaded to the industrial control system in a timely and accurate manner.

[0063] Industrial control system 4 is configured to process image data and determine the state of tobacco leaves. Based on the determined state of tobacco leaves, it outputs control signals and warning signals. Industrial control system 4 is equipped with a high-performance processor and a large-capacity memory. Monitoring software runs on industrial control system 4 to perform image processing and data analysis.

[0064] Those skilled in the art will clearly understand that the technical solutions of the embodiments of this application can be implemented by means of software and / or hardware.

[0065] In addition, the device also includes an alarm device 5. The industrial control system 4 is electrically connected to the alarm device 5. Preferably, the alarm device 5 is an audible and visual alarm device, which issues an alarm based on the monitoring results such as the presence or absence of materials, movement status, height, mesh blockage, and flow fluctuation, so as to ensure that operators can detect problems and take measures in a timely manner.

[0066] In this specification, terms such as "one embodiment," "another embodiment," "embodiment," and "preferred embodiment" refer to specific features, structures, or characteristics described in connection with that embodiment, which are included in at least one embodiment described in the general description of this application. The appearance of the same term in multiple places in the specification does not necessarily refer to the same embodiment. Furthermore, when a specific feature, structure, or characteristic is described in connection with any embodiment, the intention is to suggest that implementing such a feature, structure, or characteristic in conjunction with other embodiments also falls within the scope of this invention.

[0067] Although the invention has been described herein with reference to several illustrative embodiments, it should be understood that many other modifications and implementations can be devised by those skilled in the art, which will fall within the scope and spirit of the principles disclosed herein. More specifically, various modifications and improvements can be made to the components or layout of the subject matter arrangement within the scope of the disclosure, drawings, and claims. Besides modifications and improvements to the components or layout, other uses will be apparent to those skilled in the art.

Claims

1. A method of online monitoring of a leaf threshing and conditioning plant, characterized in that: include: Collect images of tobacco leaves at each workstation; The acquired analog image signals are converted into digital signals; To transmit digital signals; The image data is processed and the tobacco leaf condition is determined. Based on the determined tobacco leaf condition, control signals and warning signals are output. The tobacco leaf condition includes the presence or absence of material, the height of material, the movement of material, the clogging status of the vibrating screen mesh, and the fluctuation coefficient of material.

2. The online monitoring method for leaf re-baking according to claim 1, characterized in that: The process of processing image data and determining the state of tobacco leaves involves, when determining the presence or absence of material, firstly, the acquired image is converted to grayscale, and then an appropriate grayscale threshold is set to distinguish the material from the background. When the grayscale threshold is reached, it is determined that material is present.

3. The online monitoring method for leaf re-baking according to claim 1, characterized in that: The image data processing and tobacco leaf condition determination involves image segmentation to determine the material height. This segmentation isolates the material area from the image, and then calculates the pixel count or area of ​​the material area. Combined with known storage cabinet dimensions and camera parameters such as shooting angle and focal length, the actual height of the material is calculated using geometric relationships. The formula for this height is as follows: ; In this formula, This refers to the actual height of the leaf storage cabinet. Determine the installation height of the camera. The pixel height of the material in the image, α represents the vertical pixel resolution of the image, and α represents the vertical viewing angle of the camera.

4. The online monitoring method for leaf re-baking according to claim 1, characterized in that: The image data is processed to determine the state of the tobacco leaves. The movement of the material is assessed using a frame difference method, which processes consecutive image frames to calculate the positional change of the material between adjacent frames. By setting a displacement threshold, when the displacement of the material between two frames exceeds this threshold, the material is determined to be in a moving state; otherwise, it is determined to be stationary. The formula for its movement speed is as follows: ; In this formula, The time interval between two adjacent frames. This represents the number of pixels the material has shifted in the image. The horizontal pixel resolution of the image, and the horizontal field of view of the β camera. This represents the actual speed at which the material moves.

5. The online monitoring method for leaf re-baking according to claim 1, characterized in that: The image data is processed to determine the state of the tobacco leaves, wherein the formula for the material fluctuation coefficient is as follows: ； In this formula, Let Q1 be the flow rate fluctuation coefficient, Q2 be the flow rate at time t1, and Q2 be the flow rate at time t2. It is the time interval between two adjacent frames, i.e., the difference between t1 and t2; when When the threshold is exceeded, it is determined to be an abnormal flow fluctuation.

6. The online monitoring method for leaf re-baking according to claim 1, characterized in that: The process of processing image data and determining the state of tobacco leaves includes determining the clogging status of the vibrating screen mesh. This involves performing texture analysis on the image of the vibrating screen material, extracting texture features from the image to determine the uniformity of the material distribution and the clogging status of the mesh. The texture features of the image include the energy, contrast, and correlation of the gray-level co-occurrence matrix.

7. An online monitoring device for leaf re-baking, characterized in that: include A CCD high-definition camera (1) is used to collect images of tobacco leaves at each workstation; Image acquisition card (2) is used to convert the acquired analog image signals into digital signals; The wireless communication module (3) is used to transmit digital signals. The industrial control system (4) is configured to process image data and determine the tobacco leaf status, and output control signals and warning signals according to the determined tobacco leaf status.

8. The online monitoring device for leaf re-baking according to claim 7, characterized in that: The CCD high-definition camera (1) is respectively installed on the conveyor belt, the leaf storage cabinet and the vibrating screen, and the industrial control system (4) is electrically connected to the conveyor belt, the leaf storage cabinet and the vibrating screen respectively.

9. The online monitoring device for leaf re-baking according to claim 7, characterized in that: It also includes an alarm device (5), and the industrial control system (4) is electrically connected to the alarm device (5).

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