Intelligent monitoring and early warning method and system for running state of chute feed port

Abstract

The invention discloses an intelligent monitoring and early warning method and system for the running state of a chute feeding port, and belongs to the technical field of feeding port running monitoring. The intelligent monitoring and early warning method comprises the following steps: acquiring image data of a chute feed port in a running state in real time, and selecting a frame of chute feed port edge image feature stable region from the image data as a template; determining an adjustment factor of the video detection frame based on the actual working condition data and the monitoring requirement of the chute feed port; dividing image data acquired in real time into a plurality of frames of static images by the regulation factor, and comparing the current frame with the template based on a template matching algorithm to generate a similarity matrix; the maximum matching value in the similarity matrix is analyzed, and whether the running state of the chute feeding port is abnormal or not is judged; and when the operation state is abnormal, an early warning signal is sent out. The method has the remarkable characteristics of high precision, high response speed and high reliability, and provides a new thought and solution for equipment monitoring and safety early warning in the industrial production process.

Description

Technical Field

[0001] The invention belongs to the technical field of feed port operation monitoring, and relates to an intelligent monitoring and early warning method and system for the operation status of a chute feed port. Background Art

[0002] In the traditional chute feed port operation status detection process, manual inspection has long been relied on as the main means, and this practice has exposed many shortcomings and limitations in practical applications. As a traditional monitoring method, manual inspection relies heavily on the personal experience and sense of responsibility of the inspectors, which makes it difficult to effectively guarantee the accuracy and reliability of the monitoring results. Since manual inspection cannot achieve all-weather, uninterrupted real-time monitoring, once the feed port fails or is blocked, it is often impossible to find and deal with it in time, which may cause the problem to deteriorate further and bring greater potential risks to production. When the feed port is blocked, due to the lack of an automated instant response mechanism, the belt drive system of the feed port will continue to operate and continuously transport materials to the blocked feed port. This continuous material transportation undoubtedly aggravates the degree of blockage of the feed port, causing the material accumulation problem to become more serious. The consequences of material accumulation are multifaceted and often very serious. From the perspective of labor costs and production efficiency, manually cleaning the blocked feed port is a time-consuming and laborious task. Cleaning personnel not only need to invest a lot of time and energy, but also need to use various professional tools to complete the cleaning operation. This not only significantly increases labor costs, but also seriously restricts the improvement of production efficiency. In addition, chute blockage will cause the entire production process to stagnate, further delaying production progress and posing a serious challenge to economic benefits.

[0003] Although there are some fault detection methods that use simple sensors for monitoring, the information these sensors can provide is very limited and often cannot fully and accurately reflect the actual operating status of the feed port. In addition, the stability and reliability of these sensors in harsh environmental conditions also face severe challenges. In harsh environments such as high-intensity vibration, high temperature, and high humidity, sensors may fail or their accuracy may decrease, thus affecting the accuracy and reliability of the monitoring results. Summary of the invention

[0004] The purpose of the present invention is to solve the technical problem that the operating status of the chute feed port is generally detected by manual inspection or simple sensor monitoring in the prior art, and the accuracy and reliability of the monitoring results are low, and to provide an intelligent monitoring and early warning method and system for the operating status of the chute feed port.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention discloses an intelligent monitoring and early warning method for the operating status of a chute feed port, comprising:

[0007] The image data of the chute feed port in operation is collected in real time, and a frame of image feature stable area of ​​the chute feed port edge is selected as a template from the image data;

[0008] Determine the adjustment factor of the video detection frame based on the actual working condition data and monitoring requirements of the chute feed port;

[0009] The adjustment factor divides the image data collected in real time into several frames of static images, compares the current frame with the template based on the template matching algorithm, and generates a similarity matrix;

[0010] The maximum matching value in the similarity matrix is ​​analyzed to determine whether the operating state of the chute feed port is abnormal; when the operating state is abnormal, an early warning signal is issued.

[0011] Further improvements are:

[0012] The specific method of selecting a frame of image feature stable area of ​​the edge of the chute feed port from the image data as a template is as follows:

[0013] The area with stable shape, texture and color features at the edge of the chute feed port in the image data is selected as the template.

[0014] The template matching algorithm is used to compare the current frame with the template to generate a similarity matrix:

[0015] Assuming that the template image is T, the image size is m×n, the current frame image is I, and the image size is M×N, then the correlation coefficient calculation formula for each possible position (x, y) is expressed as:

[0016]

[0017]

[0018]

[0019]

[0020]

[0021] Among them, μ T represents the mean of the template image; μ Ix,y Represents the mean value of the area corresponding to the current frame; σ T Represents the standard deviation of the template image; σ Ix,yRepresents the standard deviation of the current frame image; R(x,y) represents the correlation coefficient at the pixel coordinate (x,y). The value range of R(x,y) is between -1 and 1. The closer the calculation result is to 1, the higher the maximum matching value between the template and the corresponding area of ​​the current frame.

[0022] When the maximum matching value is lower than 0.5, it is determined that the operating state of the chute feed port is abnormal.

[0023] When the first 10 consecutive static image frames of the image data are judged to be normal, and the subsequent 10 consecutive static image frames are also judged to be normal, an area with the same size as the original template is extracted from the video frame of the current image data as a new template for updating.

[0024] When the first 10 consecutive static image frames of the image data are judged to be normal, and the subsequent 10 consecutive static image frames are also judged to be normal, and the previous and next 20 static image frames simultaneously satisfy the maximum matching value higher than 0.8, an area with the same size as the original template is extracted from the video frame of the current image data as a new template for updating.

[0025] In the second aspect, the present invention discloses an intelligent monitoring and early warning system used in the intelligent monitoring and early warning method for the operating status of a chute feed port as mentioned above, comprising a camera arranged at the chute feed port, the camera signal being connected to a monitoring module, the monitoring module comprising a visual display screen and an abnormality judgment module; the abnormality judgment module being used to judge abnormal situations and to frame abnormal areas on the visual display screen.

[0026] The camera is a high-definition explosion-proof camera.

[0027] The abnormality judgment module signal is connected to an alarm device, and when it is judged that an abnormal situation occurs, the alarm device issues an alarm.

[0028] The abnormality judgment module signal is connected to a user terminal receiving module, and the user terminal receiving module is configured on a mobile terminal carried by relevant personnel to ensure that relevant personnel receive the alarm information in time.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention discloses an intelligent monitoring and early warning method for the operation status of a chute feed port. The method uses an advanced template matching algorithm, and can accurately reflect the current operation status of the chute feed port by calculating the similarity between the current frame image and the preset template in real time. Specifically, the maximum matching value in the similarity matrix becomes a key judgment basis: when the maximum matching value is high, it means that the current frame image is highly consistent with the template image, thereby indicating that the chute feed port is in a normal operation state; conversely, when the maximum matching value is low, it implies that there is a significant difference between the current frame image and the template image, which may indicate that the chute feed port has blockage, poor material flow and other abnormal conditions. This monitoring method based on the similarity matrix not only improves the accuracy of monitoring, but also makes the monitoring results more intuitive and easy to understand. Secondly, the present invention realizes flexible adjustment of the detection frame rate by introducing a video detection frame adjustment factor. In practical applications, according to the actual working condition data and monitoring requirements of the chute feed port, the adjustment factor can be reasonably set to determine the optimal detection frame rate. This design not only improves the flexibility of monitoring, but also makes the monitoring process more in line with the needs of actual production. By weighing and selecting the detection frame rate, the monitoring cost can be effectively reduced while ensuring the monitoring effect, thereby improving the overall economic benefits. Finally, the application of this intelligent monitoring and early warning method has greatly improved the monitoring efficiency of the operating status of the chute feed port. Compared with the traditional manual inspection method, this method can realize real-time monitoring and early warning of the chute feed port, and promptly detect and handle abnormal situations, thereby effectively avoiding production interruptions and safety accidents caused by equipment failures. At the same time, the automation and intelligent characteristics of this method also reduce dependence on manual intervention and improve production efficiency and safety.

[0031] Furthermore, considering the influence of the lighting environment on the image features, the present invention designs a template update optimization strategy. Specifically, when the first 10 consecutive static image frames and the subsequent 10 consecutive static image frames are judged to be normal, and the maximum matching values ​​of these frames are all higher than the set threshold (such as 0.8), the system will automatically extract an area of ​​the same size as the original template from the current video frame as a new template for update. This strategy not only ensures that the new template can accurately reflect the operating status of the current device, but also avoids the problem of system instability caused by frequent updates by maintaining the stability of the template. Through the template update optimization strategy, the present invention further improves the accuracy and reliability of the algorithm's judgment of the operating status of the device. Even when the lighting conditions change, the system can quickly adapt and adjust the template to ensure the stability and consistency of the monitoring results. This design not only enhances the robustness of the system, but also provides more reliable technical support for equipment monitoring and safety warning in industrial production processes.

[0032] The present invention discloses an intelligent monitoring and early warning system for the operation status of a chute feed port. The system adopts a high-definition explosion-proof camera, which can maintain high-definition image acquisition capabilities in a complex and changeable industrial environment, and effectively improves the safety and stability of the system. This provides users with a clearer and more realistic picture of the operation status of the chute feed port, which is convenient for subsequent analysis and judgment. Through the visual display screen in the monitoring module, the user can intuitively observe the real-time operation status of the chute feed port. At the same time, the abnormal judgment module can automatically frame the abnormal area on the display screen when an abnormal situation is detected. This intuitive visual feedback method greatly improves the user's understanding and response speed of the equipment operation status. When the abnormal judgment module detects an abnormal situation, the system will immediately trigger the alarm device and perform various forms of alarms such as sound, light and electricity to ensure that relevant personnel can detect the abnormal situation at the first time. This real-time alarm mechanism provides users with valuable response time, which helps to take measures quickly to avoid potential production failures and safety risks. The system is also equipped with a user terminal receiving module, which can instantly push the alarm information to the mobile terminal carried by the relevant personnel. This remote alarm method breaks the geographical restrictions, allowing users to receive alarm information in time and take corresponding treatment measures no matter where they are. In addition, users can also communicate with the system in real time through mobile terminals, further improving the interactivity and practicality of the system. Combining the above characteristics, the intelligent monitoring and early warning system proposed by the present invention not only improves the monitoring efficiency of the operating status of the chute feed port, but also ensures the accuracy of the monitoring results through advanced algorithms and hardware support. This provides users with more reliable and comprehensive equipment operating status information, which helps to formulate more scientific production plans and maintenance strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 It is a flow chart of an intelligent monitoring and early warning method for the operating status of a chute feed port in the present invention;

[0035] FIG2( a ) is a state diagram of the chute feed port when the stone crusher is not running in an embodiment of the present invention;

[0036] FIG2( b ) is a diagram showing the material conveying state when the equipment is running in an embodiment of the present invention;

[0037] FIG2( c ) is a working state diagram of the chute feed port when the stone crusher is operating normally in an embodiment of the present invention;

[0038] Figure 3 It is a template image of the stable area of ​​the feed port edge image feature in an embodiment of the present invention;

[0039] FIG4( a ) is a diagram showing the state detection result of the stone crusher during normal operation;

[0040] Fig. 4(b) is a diagram showing the judgment result of the operating state of the crusher under the influence of dust during the detection process when the maximum matching value threshold is set to 0.9;

[0041] Figure 4(c) is a diagram of sending alarm information to a mobile terminal;

[0042] Figure 5 This is a module diagram of an electronic device in the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0044] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0046] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0047] See also Figure 1 The embodiment of the present invention discloses an intelligent monitoring and early warning method for the operation status of a chute feed port, comprising:

[0048] S1, collecting image data of the chute feed port in operation in real time, and selecting a frame of image feature stable area of ​​the chute feed port edge image from the image data as a template;

[0049] S2, determining the adjustment factor of the video detection frame based on the actual working condition data of the chute feed port and the monitoring requirements;

[0050] S3, the adjustment factor divides the image data collected in real time into several frames of static images, compares the current frame with the template based on the template matching algorithm, and generates a similarity matrix;

[0051] S4, analyzing the maximum matching value in the similarity matrix to determine whether the operating state of the chute feed port is abnormal; when the operating state is abnormal, issuing a warning signal.

[0052] The present invention discloses an intelligent monitoring and early warning method for the operation status of a chute feed port. The method uses an advanced template matching algorithm, and can accurately reflect the current operation status of the chute feed port by calculating the similarity between the current frame image and the preset template in real time. Specifically, the maximum matching value in the similarity matrix becomes a key judgment basis: when the maximum matching value is high, it means that the current frame image is highly consistent with the template image, thereby indicating that the chute feed port is in a normal operation state; conversely, when the maximum matching value is low, it implies that there is a significant difference between the current frame image and the template image, which may indicate that the chute feed port has blockage, poor material flow and other abnormal conditions. This monitoring method based on the similarity matrix not only improves the accuracy of monitoring, but also makes the monitoring results more intuitive and easy to understand. Secondly, the present invention realizes flexible adjustment of the detection frame rate by introducing a video detection frame adjustment factor. In practical applications, according to the actual working condition data and monitoring requirements of the chute feed port, the adjustment factor can be reasonably set to determine the optimal detection frame rate. This design not only improves the flexibility of monitoring, but also makes the monitoring process more in line with the needs of actual production. By weighing and selecting the detection frame rate, the monitoring cost can be effectively reduced while ensuring the monitoring effect, thereby improving the overall economic benefits. Finally, the application of this intelligent monitoring and early warning method has greatly improved the monitoring efficiency of the operating status of the chute feed port. Compared with the traditional manual inspection method, this method can realize real-time monitoring and early warning of the chute feed port, and promptly detect and handle abnormal situations, thereby effectively avoiding production interruptions and safety accidents caused by equipment failures. At the same time, the automation and intelligent characteristics of this method also reduce dependence on manual intervention and improve production efficiency and safety.

[0053] The present method is described in detail below through specific embodiments:

[0054] Step 1: Image acquisition and template determination

[0055] Referring to Figure 2(a), Figure 2(b) and Figure 2(c), a high-definition explosion-proof camera is used to collect the operating status of the chute feed port in real time, and the real-time collected image data is transmitted to the monitoring system. The area with stable features such as shape, texture, and color of the feed port edge image is selected as a template, and the size and position of the template are further clarified to provide an accurate reference for subsequent template matching and status judgment, such as Figure 3 shown.

[0056] Step 2: Video detection interval adjustment

[0057] In order to improve detection efficiency, set the video detection frame interval adjustment factor. By adjusting the interval of the detection frame, real-time detection of different frame rates can be achieved. According to actual needs and equipment performance, reasonably adjust the detection frame rate to improve detection efficiency.

[0058] Step 3: Template matching and state judgment

[0059] The template matching algorithm is used to search for areas similar to the template in the current frame, and the operating status of the device is accurately judged by analyzing the maximum matching value in the similarity matrix. The specific calculation process can be expressed as follows: assuming that the template image is T, the image size is m×n, the current frame image is I, and the image size is M×N, then the correlation coefficient calculation formula for each possible position (x, y) can be expressed as:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] Among them, μ T represents the mean of the template image; μ Ix,y Represents the mean value of the area corresponding to the current frame; σ T Represents the standard deviation of the template image; σ Ix,y Represents the standard deviation of the current frame image; R(x,y) represents the correlation coefficient at the pixel coordinate (x,y). The value range of R(x,y) is from -1 to 1. The closer the calculation result is to 1, the higher the matching degree between the template and the corresponding area of ​​the current frame.

[0066] Step 4: Template update and optimization

[0067] In order to reduce the impact of the lighting environment on the accuracy of the algorithm detection, a template update optimization strategy is designed. When the video detection results show that the first 10 consecutive frames are normal, and the detection results of the next 10 consecutive frames are also normal, and at the same time, when the maximum matching value is higher than 0.8 during the detection process, from the current video frame that meets the conditions, according to the preset template position and size parameters, extract the area with the same size as the original template as the new template for update operation. Through such an optimization strategy, it can better adapt to the monitoring of equipment operation status under different lighting conditions, thereby significantly improving the accuracy and reliability of the algorithm's judgment of the equipment operation status.

[0068] Step 5: Exception handling and alarms

[0069] As shown in Figure 4(a), in the process of monitoring the equipment operation status, the maximum matching value in the similarity matrix is ​​used as the key judgment indicator. The similarity matrix is ​​calculated by the template matching algorithm and reflects the similarity between the current frame and the preset template. The maximum matching value can intuitively reflect the closeness between the equipment operation status and the normal state. When the maximum matching value is lower than 0.5, it means that the maximum matching value does not meet the standard of the normal state, and the detection result is displayed as an abnormal state. In order to present the abnormal situation more intuitively, a red rectangular frame is used to visualize the abnormal result so that relevant personnel can quickly locate the problem, as shown in Figure 4(b). At the same time, the system will generate an alarm signal, which can provide trigger signals for various forms of alarm devices such as sound alarms and flashing indicator lights to attract the attention of on-site staff. And in order to ensure that the abnormal situation can be handled in time, the system will push the alarm information to the relevant personnel through WeChat or other receiving terminals in time, ensuring that the relevant personnel can receive the alarm information as soon as possible no matter where they are, so that they can quickly take corresponding treatment measures to ensure the normal operation of the equipment and the smooth progress of production, as shown in Figure 4(c).

[0070] The present invention also discloses an intelligent monitoring and early warning system used in the intelligent monitoring and early warning method for the operating status of the chute feed port as described above, characterized in that it includes a camera arranged at the chute feed port, and the camera is a high-definition explosion-proof camera; the camera signal is connected to a monitoring module, and the monitoring module includes a visual display screen and an abnormality judgment module; the abnormality judgment module is used to judge abnormal situations and frame abnormal areas on the visual display screen. The abnormality judgment module signal is connected to an alarm device, and when it is judged that an abnormal situation occurs, the alarm device issues an alarm. The abnormality judgment module signal is connected to a user terminal receiving module, and the user terminal receiving module is configured on a mobile terminal carried by relevant personnel to ensure that relevant personnel receive alarm information in a timely manner.

[0071] See also Figure 5The third object of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the intelligent monitoring and early warning method for the operating status of the chute feed port are implemented.

[0072] The intelligent monitoring and early warning method for the operating status of the chute feed port comprises the following steps:

[0073] Collect image data of the chute feed port in operation in real time, and select a static image frame from the image data as a template;

[0074] Determine the adjustment factor of the video detection frame based on the actual working condition data and monitoring requirements of the chute feed port;

[0075] The adjustment factor divides the image data collected in real time into several frames of static images, compares the current frame with the template based on the template matching algorithm, and generates a similarity matrix;

[0076] The maximum matching value in the similarity matrix is ​​analyzed to determine whether the operating state of the chute feed port is abnormal; when the operating state is abnormal, an early warning signal is issued.

[0077] The fourth object of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the intelligent monitoring and early warning method of the operating status of the chute feed port are implemented.

[0078] The intelligent monitoring and early warning method for the operating status of the chute feed port comprises the following steps:

[0079] Collect image data of the chute feed port in operation in real time, and select a static image frame from the image data as a template;

[0080] Determine the adjustment factor of the video detection frame based on the actual working condition data and monitoring requirements of the chute feed port;

[0081] The adjustment factor divides the image data collected in real time into several frames of static images, compares the current frame with the template based on the template matching algorithm, and generates a similarity matrix;

[0082] The maximum matching value in the similarity matrix is ​​analyzed to determine whether the operating state of the chute feed port is abnormal; when the operating state is abnormal, an early warning signal is issued.

[0083] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0085] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0086] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0087] The working principle of the present invention is as follows:

[0088] First, real-time and accurate monitoring

[0089] (1) A high-resolution explosion-proof camera is reasonably arranged at the chute feed port. This camera has strong anti-interference ability and can work stably in complex environments, ensuring comprehensive and clear real-time acquisition of the feed port operation status. Whether in harsh environmental conditions or facing various interference factors, it can continuously provide high-quality image data for the monitoring system.

[0090] (2) The advanced template matching algorithm calculates the similarity between the current frame and the predetermined template and combines the maximum matching value to determine the equipment operation status. This method can carefully analyze every detail in the image and accurately identify the state changes of the feed port. It can also keenly capture the slightest anomaly in the operation of the equipment, making the judgment result more accurate and reliable, providing a solid guarantee for enterprises to promptly discover potential problems and take preventive measures.

[0091] Second, adapt to changes in lighting

[0092] Taking into full consideration the impact of the lighting environment on detection accuracy, the present invention has designed an ingenious template update optimization strategy. Under different lighting conditions, the image's brightness, contrast, color and other features will change. This strategy can adjust the template in time according to the changes in lighting, ensuring that the detection algorithm can always accurately identify the state of the feed port.

[0093] Third, efficient and flexible detection

[0094] The designed video detection frame interval adjustment factor provides great flexibility for enterprises. According to actual needs and equipment performance, enterprises can freely adjust the interval of detection frames to achieve real-time detection at different frame rates. This enables enterprises to optimize according to specific circumstances and achieve the best detection effect in different scenarios.

[0095] Fourth, timely exception handling

[0096] (1) The present invention has an abnormality handling and alarm mechanism. When the detection result is abnormal, a red rectangular frame is used to visualize the abnormal frame, so that relevant personnel can intuitively see the location of the abnormal situation at the first time.

[0097] (2) At the same time, it can provide alarm signals for various alarm devices such as sound and light, and send the alarm information including the abnormality type, occurrence time, location and other details to relevant personnel via WeChat, so that relevant personnel can quickly take targeted response measures.

[0098] (3) Timely notification of relevant personnel to handle the situation can effectively avoid further deterioration of abnormal situations, providing strong technical support for the enterprise's safe production management. By quickly responding to and handling abnormal situations, the risk of equipment damage and production losses can be minimized, production efficiency can be improved, and the normal production operation of the enterprise can be guaranteed.

[0099] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent monitoring and early warning method for the operating status of a chute feed port, characterized in that: include: The image data of the chute feed port in operation is collected in real time, and a frame of image feature stable area of ​​the chute feed port edge is selected as a template from the image data; Determine the adjustment factor of the video detection frame based on the actual working condition data and monitoring requirements of the chute feed port; The adjustment factor divides the image data collected in real time into several frames of static images, compares the current frame with the template based on the template matching algorithm, and generates a similarity matrix; Analyze the maximum matching value in the similarity matrix to determine whether the operating state of the chute feed port is abnormal; When the operating status is abnormal, an early warning signal is issued.

2. The intelligent monitoring and early warning method for the operation status of the chute feed port according to claim 1 is characterized in that: The specific method of selecting a frame of image feature stable area of ​​the edge of the chute feed port from the image data as a template is as follows: The area with stable shape, texture and color features at the edge of the chute feed port in the image data is selected as the template.

3. The intelligent monitoring and early warning method for the operation status of the chute feed port according to claim 1 is characterized in that: The template matching algorithm is used to compare the current frame with the template to generate a similarity matrix: Assuming that the template image is T, the image size is m×n, the current frame image is I, and the image size is M×N, then the correlation coefficient calculation formula for each possible position (x, y) is expressed as: Among them, μ T represents the mean of the template image; Represents the mean value of the area corresponding to the current frame; σ T Represents the standard deviation of the template image; Represents the standard deviation of the current frame image; R(x,y) represents the correlation coefficient at the pixel coordinate (x,y). The value range of R(x,y) is between -1 and 1. The closer the calculation result is to 1, the higher the maximum matching value between the template and the corresponding area of ​​the current frame.

4. The intelligent monitoring and early warning method for the operation status of the chute feed port according to claim 1 is characterized in that: When the maximum matching value is lower than 0.5, it is determined that the operating state of the chute feed port is abnormal.

5. The intelligent monitoring and early warning method for the operation status of the chute feed port according to claim 1 is characterized in that: When the first 10 consecutive static image frames of the image data are judged to be normal, and the subsequent 10 consecutive static image frames are also judged to be normal, an area with the same size as the original template is extracted from the video frame of the current image data as a new template for updating.

6. The intelligent monitoring and early warning method for the operation status of the chute feed port according to claim 5 is characterized in that: When the first 10 consecutive static image frames of the image data are judged to be normal, and the subsequent 10 consecutive static image frames are also judged to be normal, and the previous and next 20 static image frames simultaneously satisfy the maximum matching value higher than 0.8, an area with the same size as the original template is extracted from the video frame of the current image data as a new template for updating.

7. An intelligent monitoring and early warning system used in the intelligent monitoring and early warning method for the operation status of a chute feed port according to any one of claims 1 to 6, characterized in that: It includes a camera arranged at the feeding port of the chute, wherein the camera signal is connected to a monitoring module, and the monitoring module includes a visual display screen and an abnormality judgment module; the abnormality judgment module is used to judge the abnormal situation and select the abnormal area on the visual display screen.

8. The intelligent monitoring and early warning system for the operation status of the chute feed port according to claim 7 is characterized in that: The camera is a high-definition explosion-proof camera.

9. The intelligent monitoring and early warning system for the operation status of the chute feed port according to claim 7 is characterized in that: The abnormality judgment module signal is connected to an alarm device, and when it is judged that an abnormal situation occurs, the alarm device issues an alarm.

10. The intelligent monitoring and early warning system for the operation status of the chute feed port according to claim 7, characterized in that: The abnormality judgment module signal is connected to a user terminal receiving module, and the user terminal receiving module is configured on a mobile terminal carried by relevant personnel to ensure that relevant personnel receive the alarm information in time.

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