Belt type pellet roasting abnormity processing method and device, electronic equipment and medium

Abstract

The invention relates to a belt type pellet roasting exception handling method, device and equipment and a medium. The method comprises the following steps: acquiring operation data in a belt type pellet roasting system; according to the theoretical life value and the service life value of each assembly, determining the static safety coefficient of the assembly; determining a dynamic safety coefficient according to the roasting parameter change rate of each component; determining a reference safety coefficient according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety coefficient, the dynamic safety coefficient and / or the reference safety coefficient; inputting the operation data into the target detection model to obtain a second detection result; determining a target detection result according to the first detection result and / or the second detection result; and under the condition that the target detection result represents that the belt type pellet roasting system is abnormal, the belt type pellet roasting system is controlled according to a control mode matched with the abnormal grade. In this way, the whole production line can keep high stability and continuity.

Description

Technical Field

[0001] The present application relates to the technical field of abnormal handling of belt-type pellet roasting, and in particular to a method, device, electronic equipment and medium for abnormal handling of belt-type pellet roasting. Background Art

[0002] In a belt pelletizing system, the safe and stable operation of equipment is crucial for ensuring continuous production. Because this system typically consists of dozens to hundreds of interconnected pieces of equipment, covering multiple process steps such as raw material transportation, pelletizing, roasting, cooling, screening, and dust removal, any failure in any piece of equipment can have a cascading impact on the entire production line, leading to production interruptions, product quality fluctuations, and even safety incidents.

[0003] Despite the continuous advancement of modern metallurgical equipment technology and the significant increase in equipment reliability, unexpected equipment failures remain difficult to completely avoid during actual operation. In such situations, how to quickly and appropriately adjust the operating status of remaining equipment after a failure occurs to minimize the impact on overall production becomes a key issue in ensuring system operational resilience and economic efficiency.

[0004] Currently, the industry generally relies on experienced operators to make manual judgments and interventions based on on-site conditions. For example, when a piece of equipment fails, the operator, based on experience, decides whether to shut down the machine, reduce its speed, switch to backup equipment, or adjust upstream and downstream process parameters. However, this approach has significant limitations, including limited response speed, varying experience and decision-making levels among operators, poor consistency in response, and difficulty in standardization. Summary of the Invention

[0005] Based on this, it is necessary to provide a method, device, electronic equipment and medium for handling belt pellet roasting anomalies in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for handling belt pellet roasting anomalies, the method comprising: Obtain operating data in the belt pellet roasting system; Based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result; wherein, the target detection result includes at least one of whether there is an abnormality, abnormality location, abnormality type and abnormality level; based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result, including: determining the static safety factor of the component according to the theoretical life value and service life value of each component in the belt pellet roasting system; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operating data into the target detection model to obtain a second detection result; determining the target detection result according to the first detection result and / or the second detection result; When the target detection result indicates that an abnormality occurs in the belt-type pellet roasting system, the belt-type pellet roasting system is controlled according to a control mode that matches the abnormality level.

[0007] In one embodiment, the structure of the target detection model includes an input end, a backbone network, a neck network and a prediction end.

[0008] In one embodiment, determining the dynamic safety factor according to the rate of change of the firing parameters of each component includes: determining a rate of change of the firing parameter based on a measured value and a reference value of the firing parameter of the component; The safety assessment value of each component is determined, and the dynamic safety factor is determined based on the firing parameter change rate of each component and the corresponding safety assessment value.

[0009] In one embodiment, controlling the belt pellet roasting system according to a control mode matching the abnormality level includes: In the case where the abnormality level is a first-level response, a corresponding compensation control mode is determined according to the abnormality type; wherein the first-level response indicates that the belt pellet roasting system has an operational abnormality; According to the compensation control mode, the roasting parameters corresponding to the abnormal type are adjusted until the production requirements are met.

[0010] In one embodiment, the belt-type pellet roasting system includes at least a green pellet transport subsystem, a roasting subsystem, and a combustion-supporting subsystem; the roasting subsystem includes a roasting assembly; the combustion-supporting subsystem includes a combustion-supporting fan and a burner; and controlling the belt-type pellet roasting system according to a control mode matching the abnormality level includes: When the abnormality level is a secondary response, the roasting parameters of specific components in the belt pellet roasting system are adjusted according to the low fire mode until the setting conditions corresponding to the low fire mode are met; wherein, the secondary response indicates that there is a mechanical abnormality in the belt pellet roasting system; the setting conditions include that the temperature parameter of the roasting component is less than a first threshold, the operating speed of the roasting component is less than a second threshold, the operating frequency of the combustion-supporting fan is less than a third threshold and / or the green pellet transmission subsystem is in a shutdown state.

[0011] In one embodiment, controlling the belt pellet roasting system according to a control mode matching the abnormality level includes: When the abnormality level is level three, an emergency sequential shutdown strategy is established based on the abnormality location and production process; wherein, the level three response indicates that the safety risk of the belt pellet roasting system is greater than the warning level; According to the emergency sequential shutdown strategy, the belt pellet roasting system is controlled to enter a shutdown state.

[0012] In one embodiment, the belt-type pellet roasting system includes a low-fire mode control button and a shutdown mode control button; the method further includes at least one of the following: When a trigger operation on the low fire mode control button is received, the belt-type pellet roasting system is controlled to enter the low fire mode through the low fire mode control button; When a trigger operation on the shutdown mode control button is received, the belt-type pellet roasting system is controlled to enter the shutdown mode through the shutdown mode control button.

[0013] In a second aspect, the present application further provides a belt-type pellet roasting abnormality treatment device, the device comprising: An acquisition module is used to obtain operating data in the belt pellet roasting system; A detection module is configured to detect the safety status of the belt-type pellet roasting system based on the operation data through a first detection algorithm and / or a second detection algorithm to obtain a target detection result; wherein the target detection result includes at least one of whether there is an abnormality, abnormality location, abnormality type and abnormality level; the detection of the safety status of the belt-type pellet roasting system based on the operation data through the first detection algorithm and / or the second detection algorithm to obtain a target detection result includes: determining the static safety factor of each component in the belt-type pellet roasting system according to the theoretical life value and service life value of each component; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operation data into a target detection model to obtain a second detection result; determining the target detection result according to the first detection result and / or the second detection result; The control module is configured to control the belt pellet roasting system according to a control mode matching the abnormality level when the target detection result indicates that the belt pellet roasting system is abnormal.

[0014] In a third aspect, the present application also provides an electronic device comprising a processor and a memory for storing a computer program for the processor; wherein the processor is configured to: when executing the computer program, implement the steps of the method execution described in any embodiment of the present application.

[0015] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method execution described in any embodiment of the present application.

[0016] The aforementioned belt pellet roasting anomaly handling method, on the one hand, enables real-time monitoring and early warning of equipment status through the continuous collection and analysis of operating data. The target detection results not only indicate whether an anomaly has occurred, but also precisely locate the anomaly, identify the anomaly type, and assess the anomaly level, enabling rapid and accurate identification of the problem and facilitating timely resolution. Furthermore, compared to manual judgment and intervention, automated detection and control enable a response in the shortest possible time, minimizing the time required to repair a fault and restore normal production. Furthermore, by adopting appropriate control modes based on different anomaly levels, the entire production line can maintain a high level of stability and continuity even in the event of partial equipment failure. For example, minor anomalies can be overcome through local adjustments, while major failures require the activation of comprehensive emergency response plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of a method for handling belt-type pellet roasting anomalies according to an exemplary embodiment; Figure 2 is a structural schematic diagram of a belt-type pellet roasting system according to an exemplary embodiment; Figure 3 is a schematic diagram showing abnormal positioning of a belt-type pellet roasting system according to an exemplary embodiment; Figure 4 is a flow chart of a method for handling belt-type pellet roasting anomalies according to an exemplary embodiment; Figure 5 is a structural block diagram of a belt-type pellet roasting abnormality processing device according to an exemplary embodiment; Figure 6 It is a diagram showing the internal structure of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0019] The terms "first", "second" and "third" in the embodiments of the present application are only used for descriptive purposes and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second" and "third" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, method, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally also include steps or units that are not listed, or may optionally also include other steps or units inherent to these processes, methods, products or devices.

[0020] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0021] In some embodiments, the belt pellet roasting exception handling method provided in the embodiments of the present application can be applied to an electronic device or a cloud server. Among them, the electronic device can be any mobile terminal or fixed terminal. The terminal can be a device that provides voice and / or data connectivity to the user. Exemplarily, the terminal can be an Internet of Things terminal, such as a sensor device, a mobile phone or a so-called "cellular" phone and a computer with an Internet of Things terminal, for example, it can be a fixed, portable, pocket-sized, handheld, or computer-built-in device. The cloud server can be any virtualized computing resource or physical server cluster. The server can be a platform that provides on-demand, scalable computing, storage, network and application services to users.

[0022] In some embodiments, as Figure 1 As shown, a method for handling belt pellet roasting abnormalities is provided, the method comprising the following steps: S101, obtaining operating data in the belt pellet roasting system.

[0023] In the embodiment of the present application, the belt pellet roasting system may include but is not limited to at least one of a base material subsystem, a combustion-supporting subsystem, a green pellet transmission subsystem, a finished product transmission subsystem, a roasting subsystem and a hot air circulation subsystem.

[0024] For example, Figure 2 As shown, Figure 2 Schematic diagram of the structure of the belt pellet roasting system.

[0025] Optionally, the bed material subsystem may include but is not limited to a plurality of bed material belt machines and a bed material bin.

[0026] Optionally, the green ball conveying subsystem may include but is not limited to a belt conveyor, a roller screen, a wide belt and a cloth trolley.

[0027] Optionally, the combustion-supporting system may include but is not limited to a combustion-supporting blower and multiple pairs of burner groups.

[0028] Optionally, the roasting subsystem may include but is not limited to a roasting machine main drive and a trolley.

[0029] Optionally, the hot air circulation subsystem may include but is not limited to a furnace hood, main extraction, heat recovery, air drying and cooling process fans.

[0030] In the embodiments of the present application, the operating data indicates various operating parameters of the belt pellet roasting system throughout the entire process, from raw material processing to finished product output. The operating data may include, but is not limited to, at least one of raw material and green pellet data, temperature data, pressure data, flow data, vibration and noise data, electrical parameter data, equipment status data, and other process-related data.

[0031] Optionally, the raw material and green ball related data may include but are not limited to at least one of raw material composition, green ball size, green ball moisture content and green ball strength.

[0032] Optionally, the temperature-related data may include but is not limited to at least one of the preheating section temperature, the roasting section temperature, the cooling section temperature and the exhaust gas temperature.

[0033] Optionally, the pressure-related data may include but is not limited to at least one of the internal pressure of the roasting furnace and the outlet pressure of the combustion-supporting fan.

[0034] Optionally, the flow-related data may include but is not limited to at least one of fuel flow, combustion-supporting air volume, exhaust gas flow and material flow (transmission speed, total transmission volume, etc.).

[0035] Optionally, the vibration and noise related data may include but is not limited to at least one of equipment vibration frequency (such as fans, motors, conveyor belts, etc.) and noise level.

[0036] Optionally, the electrical-related parameter data may include but is not limited to at least one of the operating voltage, operating current and power parameters of the electrical equipment.

[0037] Optionally, the equipment status related data may include but is not limited to at least one of operating time, fault records, lubrication status, and valve opening and closing degree.

[0038] Optionally, other process-related data may include but are not limited to at least one of green ball stacking / distribution, roasting cycle, and finished product quality indicators.

[0039] S102, based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result; wherein, the target detection result includes at least one of whether it is abnormal, abnormal location, abnormal type and abnormal level; based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result, including: determining the static safety factor of the component according to the theoretical life value and service life value of each component in the belt pellet roasting system; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operating data into the target detection model to obtain a second detection result; determining the target detection result according to the first detection result and / or the second detection result.

[0040] In some embodiments, the first detection algorithm and the second detection algorithm may be different algorithm models or preset rules. The first detection algorithm is different from the second detection algorithm.

[0041] Exemplarily, the algorithm model may include, but is not limited to, at least one of a time series analysis model (e.g., ARIMA (AutoRegressive Integrated Moving Average)), a machine learning classification model (e.g., Random Forest, Support Vector Machine (SVM)), and a deep learning model (e.g., Transformer architecture, neural network model).

[0042] Exemplarily, the preset rules may include but are not limited to at least one of statistical process control (SPC) and a threshold comparison method.

[0043] In one embodiment, Figure 3 As shown, Figure 3 This is a schematic diagram of abnormality location in a belt pellet roasting system. Abnormality location in a belt pellet roasting system may include, but is not limited to, failures in the bed material subsystem, combustion support subsystem, green pellet transport subsystem, finished product transport subsystem, roasting subsystem, and hot air circulation subsystem.

[0044] In one embodiment, the abnormality levels may include, but are not limited to, level 1 response, level 2 response, and level 3 response. A level 1 response may indicate an operational abnormality in the belt pellet roasting system, such as the roasting section temperature not reaching the expected temperature; a level 2 response may indicate a mechanical abnormality in the belt pellet roasting system, such as a partial break in the conveyor belt in the green pellet transport subsystem; and a level 3 response may indicate a safety risk greater than the warning level, requiring a production halt.

[0045] In one embodiment, the theoretical life value is equal to the sum of the service life value and the remaining life value; the belt pellet roasting system includes first to Nth components; N is a positive integer and N is greater than 1; the electronic device can determine the first first coefficient based on the ratio of the service life value of the first component (for example, the combustion-supporting fan) to the theoretical life value; determine the second first coefficient based on the ratio of the service life value of the second component to the theoretical life value; and so on, until the Nth first coefficient is determined; determine the static safety factor based on the first to Nth first coefficients.

[0046] In some embodiments, determining the dynamic safety factor according to the rate of change of the firing parameters of each component includes: determining a rate of change of the firing parameter based on a measured value and a reference value of the firing parameter of the component; The safety assessment value of each component is determined, and the dynamic safety factor is determined based on the firing parameter change rate of each component and the corresponding safety assessment value.

[0047] In the embodiments of this application, the measured value indicates the actual operating value of the component's firing parameter; the reference value indicates the theoretically desired value of the component's firing parameter. For example, if the component is a combustion-supporting fan and the firing parameter is the operating frequency, the measured value is the actual operating frequency of the combustion-supporting fan, while the reference value is the theoretically desired operating frequency of the combustion-supporting fan.

[0048] In the embodiment of the present application, the safety assessment value can be determined based on the degree of influence of each component on the safety status of the belt pellet roasting system; or, it can be determined based on the real-time operating frequency of each component; or, it can be determined based on the importance of each component to the belt pellet roasting system.

[0049] In one embodiment, the belt pellet roasting system includes first to Nth components; N is a positive integer and N is greater than 1; the electronic device can determine a first value based on the difference between the measured value of the first component and the reference value; determine the roasting parameter change rate based on the ratio of the first value to the measured value; and so on, the roasting parameter change rates of the first to Nth components can be determined in sequence; the i-th second value is determined based on the product of the roasting parameter change rate of the i-th component and the corresponding safety assessment value; and the dynamic safety factor is determined based on the sum of the first to N-th second values.

[0050] In one embodiment, the electronic device may compare the abnormal duration of abnormal signals generated by each subsystem / component in the belt pellet roasting system with a preset reference threshold value to determine a reference safety factor.

[0051] Exemplarily, the electronic device can record the duration of abnormal signals in the production transmission subsystem that characterize belt slippage, tearing, material blockage or sudden stop, as well as abnormal signals that characterize material distribution trolley failure and roller distributor failure, to determine the duration of the abnormality; when the duration of the abnormality is greater than a first reference threshold (for example, 60 minutes / min), the first safety factor can be determined to be 0.8, indicating that the production transmission subsystem has a large safety risk; when the duration of the abnormality is less than or equal to the first reference threshold and greater than the second reference threshold (such as 25 minutes), such as the duration of the abnormality is 30 minutes, the first safety factor can be determined to be 0.5, indicating that the production transmission subsystem has a moderate safety risk; when the duration of the abnormality is less than or equal to the second reference threshold, the first safety factor can be determined to be 0.2, indicating that the production transmission subsystem has a low safety risk.

[0052] For example, the electronic device can record the duration of abnormal signals in the bed material subsystem, such as those indicating belt slippage, tearing, material blockage, deviation, or sudden stop, to determine the duration of the abnormality. This abnormality can then be combined with the material level in the bed material silo to determine a second safety factor. If the abnormality duration exceeds a third reference threshold (e.g., 60 minutes) or the material level is less than a fourth reference threshold (e.g., 10%), the reference safety factor is determined to be 0.85, indicating a high safety risk for the bed material subsystem. If the abnormality duration is less than or equal to a fifth reference threshold and greater than a sixth reference threshold (e.g., 30 minutes), or the material level is greater than or equal to a fourth reference threshold and less than a seventh reference threshold (e.g., 40%), the second safety factor is determined to be 0.4, indicating a low safety risk for the bed material subsystem.

[0053] In one embodiment, when any component / subsystem in the belt pellet roasting system has a large safety risk, it will have a great impact on the production of the entire belt pellet roasting system; therefore, the electronic device can determine the maximum value of the safety factor in each subsystem as the reference safety factor.

[0054] In some embodiments, the electronic device can determine the first detection result based on any one of the static safety factor, the dynamic safety factor and the reference safety factor; or, it can determine the first detection result based on the maximum value of the static safety factor, the dynamic safety factor and the reference safety factor; or, the electronic device can also determine a third value based on the sum of the static safety factor and the dynamic safety factor; and determine the first detection result based on the product of the third value and the reference safety factor; no further limitations are given here.

[0055] In one embodiment, the operating data may be image data acquired by an image acquisition device in real time photographing each component in the belt-type pellet roasting system.

[0056] In some embodiments, the structure of the target detection model includes an input end, a backbone network, a neck network and a prediction end.

[0057] In one embodiment, when the operating data is image data, the object detection model can be a YOLO model. The object detection model can simultaneously perform object detection and classification through a single forward propagation process, thereby detecting whether there are any abnormalities in the components of the belt pellet roasting system, locating the abnormalities if any, and determining a second detection result.

[0058] In one embodiment, when either the first detection result or the second detection result indicates that the belt pellet roasting system has an abnormality, the target detection result is determined to be that the belt pellet roasting system has an abnormality; when both the first detection result and the second detection result indicate that the belt pellet roasting system has no abnormality, the target detection result is determined to be that the belt pellet roasting system has no abnormality.

[0059] In the embodiment of the present application, the static safety factor, dynamic safety factor and reference safety factor are respectively based on three different perspectives: equipment aging, operating status fluctuation and fault persistence of the belt pellet roasting system, to construct a comprehensive safety assessment system. Compared with the judgment of a single indicator, the first detection result determined is more accurate; by inputting the operating data into the target detection model, the deep features in the data can be extracted, and hidden faults that are difficult for the human eye to detect can be identified. It can also have the ability to identify new fault types; through the fusion and complementarity of the first detection result and the second detection result, the coverage and accuracy of the target detection results are improved, and the false alarm and missed alarm rates are reduced.

[0060] S103 , when the target detection result indicates that an abnormality occurs in the belt-type pellet roasting system, controlling the belt-type pellet roasting system according to a control mode that matches the abnormality level.

[0061] In the embodiment of the present application, the control mode may include but is not limited to a compensation control mode, a low-fire mode and a shutdown mode.

[0062] In an embodiment of the present application, the compensation control mode indicates that when the process is unbalanced, a preset local alternative control strategy is dynamically activated to build a temporary stable loop in the fault-affected area to achieve limited replacement and functional compensation of the main control logic.

[0063] In this embodiment of the present application, low-fire mode indicates a specific low-temperature standby mode. Low-fire mode is used to maintain hot standby, keeping the system at a low and controllable temperature, reducing energy consumption and time loss caused by restarting the equipment after complete cooling. Furthermore, low-fire mode allows for rapid temperature increase to restore to normal production, and can also switch from a low-power state to a shutdown state, reducing safety incidents caused by mechanical fault lights.

[0064] In the embodiment of the present application, the production suspension mode indicates a mode in which production activities are temporarily suspended due to reasons such as mechanical failure.

[0065] In some embodiments, the electronic device can adjust the belt pellet roasting system according to the level of the abnormality by selecting a control mode that is compatible with the abnormality level. For example, when the abnormality level is high, it indicates a greater safety risk, and a shutdown mode can be selected to reduce safety risks and production losses.

[0066] The aforementioned belt pellet roasting anomaly handling method, on the one hand, enables real-time monitoring and early warning of equipment status through the continuous collection and analysis of operating data. The target detection results not only indicate whether an anomaly has occurred, but also precisely locate the anomaly, identify the anomaly type, and assess the anomaly level, enabling rapid and accurate identification of the problem and facilitating timely resolution. Furthermore, compared to manual judgment and intervention, automated detection and control enable a response in the shortest possible time, minimizing the time required to repair a fault and restore normal production. Furthermore, by adopting appropriate control modes based on different anomaly levels, the entire production line can maintain a high level of stability and continuity even in the event of partial equipment failure. For example, minor anomalies can be overcome through local adjustments, while major failures require the activation of comprehensive emergency response plans.

[0067] In some embodiments, controlling the belt pellet roasting system according to a control mode matching the abnormality level includes: In the case where the abnormality level is a first-level response, a corresponding compensation control mode is determined according to the abnormality type; wherein the first-level response indicates that the belt pellet roasting system has an operational abnormality; According to the compensation control mode, the roasting parameters corresponding to the abnormal type are adjusted until the production requirements are met.

[0068] In one embodiment, when the abnormality level of the target detection result is a first-level response, it can be determined that the belt pellet roasting system has an operational abnormality and the safety risk is low; the electronic equipment can determine the corresponding compensation control mode based on the abnormality location and abnormality type; for example, if the abnormality type is a roasting temperature abnormality, the compensation control mode can be determined to be a temperature compensation mechanism, and the roasting temperature can be compensated for by an alternative burner or a combustion-supporting fan, and roasting parameters such as the gas flow rate or the combustion-supporting air volume can be increased to achieve the expected roasting temperature and meet production requirements.

[0069] In the embodiment of the present application, the first-level response usually means that the system is in a state of "abnormal operation but not causing serious shutdown", such as slight temperature deviation, wind pressure fluctuation, slight transmission jam, etc.; by starting the compensation control mode, key process parameters can be fine-tuned in time to avoid small faults from evolving into major accidents, and effectively curb the spread of the impact of the fault; and, the thermal balance and material flow stability during the pellet roasting process can be maintained to ensure that the quality of the final product is not affected.

[0070] In some embodiments, the belt-type pellet roasting system includes at least a green pellet transport subsystem, a roasting subsystem, and a combustion-supporting subsystem; the roasting subsystem includes a roasting assembly; the combustion-supporting subsystem includes a combustion-supporting fan and a burner; and controlling the belt-type pellet roasting system according to a control mode matching the abnormality level includes: When the abnormality level is a secondary response, the roasting parameters of specific components in the belt pellet roasting system are adjusted according to the low fire mode until the setting conditions corresponding to the low fire mode are met; wherein, the secondary response indicates that there is a mechanical abnormality in the belt pellet roasting system; the setting conditions include that the temperature parameter of the roasting component is less than a first threshold, the operating speed of the roasting component is less than a second threshold, the operating frequency of the combustion-supporting fan is less than a third threshold and / or the green pellet transmission subsystem is in a shutdown state.

[0071] In one embodiment, when the abnormality level of the target detection result does not reach the second-level response but the abnormality type is a mechanical abnormality, the electronic equipment can control the belt pellet roasting system according to the production reduction mode, for example, reducing the amount of green pellets entering the machine to 70% of the original setting, reducing the speed of the trolley and the combustion air volume of the combustion fan by 20%, etc.

[0072] In one embodiment, if the target detection result's abnormality level is a Level 2 response, it can be determined that the belt pellet roasting system has a mechanical abnormality (such as transmission jamming, excessive fan vibration, or trolley deviation). Although it has not yet reached the level of an emergency shutdown, it has affected normal continuous production. Electronic equipment can use low-fire mode to gradually adjust the system to a low-energy, low-risk, and controllable transition state to reduce the thermal shock, equipment damage, or process disruption caused by a direct shutdown. For example, the roasting component temperature parameters can be adjusted to less than a first threshold (such as 400 degrees Celsius), the roasting component operating speed can be adjusted to less than a second threshold (such as adjusting the roasting machine to the lowest operating speed), and the combustion fan operating frequency can be adjusted to less than a third threshold (such as adjusting the combustion fan operating frequency to the lowest frequency), and the green pellet transport subsystem can be stopped.

[0073] In the embodiment of the present application, controlling the belt pellet roasting system in low-fire mode can effectively respond to mechanical abnormalities, gradually adjusting the system to a low-energy, low-risk, controllable transition state, and ensuring the system's flexible degradation operation to resume production or safe shutdown. On the one hand, it can reduce the system's thermal load to reduce energy waste and protect key equipment to extend its service life; on the other hand, it can also quickly enter an emergency shutdown / shutdown state to respond to emergency / major safety risks.

[0074] In some embodiments, controlling the belt pellet roasting system according to a control mode matching the abnormality level includes: When the abnormality level is level three, an emergency sequential shutdown strategy is established based on the abnormality location and production process; wherein, the level three response indicates that the safety risk of the belt pellet roasting system is greater than the warning level; According to the emergency sequential shutdown strategy, the belt pellet roasting system is controlled to enter a shutdown state.

[0075] In one embodiment, if the abnormality level reaches Level 3, which typically indicates a serious safety risk (such as a major mechanical failure that could result in a fire or explosion), the top priority is ensuring the safety of personnel and equipment. Electronic equipment can then immediately and synchronously shut down all subsystems, entering an emergency shutdown state.

[0076] In one embodiment, the abnormality is located in the green ball transmission subsystem. The electronic equipment can determine that there are still materials to be processed in the roasting subsystem and the finished product transmission subsystem based on the production process. In this case, the green ball transmission subsystem can be cut off first, and other subsystems can be gradually shut down after completion of operation. For example, after the roasting subsystem completes the roasting of all green balls, the roasting subsystem is shut down. The finished product transmission subsystem waits for the transportation of all finished products before it is finally shut down. At the same time, the non-volatile memory is triggered to save key process parameters to ensure data integrity.

[0077] In the embodiment of the present application, the emergency sequential shutdown strategy is used to gradually shut down each subsystem in an orderly manner, thereby reducing the secondary disasters that may be caused by sudden power outages or sudden shutdowns (such as damage to high-temperature equipment due to sudden cooling, blockage caused by material accumulation, etc.); and, since disorderly shutdowns may lead to the scrapping of semi-finished products on the production line, waste of raw materials, and complication of subsequent cleanup work, the emergency sequential shutdown strategy can ensure that key process links are gradually stopped in a preset order, minimize the loss of unfinished products, and create conditions for the rapid resumption of production.

[0078] In some embodiments, the belt-type pellet roasting system includes a low-fire mode control button and a shutdown mode control button; the method further includes at least one of the following: When a trigger operation on the low fire mode control button is received, the belt-type pellet roasting system is controlled to enter the low fire mode through the low fire mode control button; When a trigger operation on the shutdown mode control button is received, the belt-type pellet roasting system is controlled to enter the shutdown mode through the shutdown mode control button.

[0079] In some embodiments, the belt pellet roasting system can also be semi-automatically controlled through human intervention. The operator can make judgments based on the actual operation of the belt pellet roasting system and the output target detection results. By clicking the low-fire mode control button, the roasting parameters of specific components in the belt pellet roasting system can be adjusted to control the belt pellet roasting system to enter the low-fire mode; by clicking the shutdown mode control button, the belt pellet roasting system can be shut down in an emergency to ensure system safety.

[0080] In the embodiment of the present application, by retaining the manual intervention interface on the basis of the system having the ability of automatic detection and analysis, the operator can manually trigger the low-fire mode or the shutdown mode according to the target detection results of the system and the actual situation on site. In an emergency (such as sudden equipment jamming, high temperature alarm, smoke leakage, etc.), even if the system has not yet reached the standard for automatically triggering a third-level response, the operator can also quickly shut down the system by clicking the "shutdown mode control button", thereby achieving flexible response in complex industrial scenarios and meeting safety protection needs.

[0081] In the embodiments of the present application, the following provides specific examples in combination with any of the above embodiments: Specific example 1: Figure 4 This is a schematic diagram showing an exemplary process for implementing the belt pellet roasting abnormality treatment method provided in any embodiment of the present application, as shown in FIG. Figure 4 As shown, the steps of executing the belt pellet roasting abnormality processing method in the electronic device are as follows: S401, determining whether an abnormal condition occurs in the belt pellet roasting system.

[0082] In an optional embodiment, the electronic device may determine whether an abnormality occurs in the belt pellet roasting system based on the target detection result. If so, the process proceeds to S402; if not, the process ends.

[0083] S402, determining whether the belt pellet roasting system adopts an automatic control strategy.

[0084] In an optional embodiment, if yes, proceed to S404; if no, proceed to S403.

[0085] S403, determining whether the belt pellet roasting system adopts a semi-automatic control strategy.

[0086] In an optional embodiment, if yes, proceed to S405; if no, end the process.

[0087] S404: Control the belt pellet roasting system according to a control mode that matches the abnormality level.

[0088] S405: Receive the triggering operation of the low fire mode control button by the operator.

[0089] In an optional embodiment, when a trigger operation on the low fire mode control button is received, the belt-type pellet roasting system is controlled to enter the low fire mode through the low fire mode control button.

[0090] S406: Receive the operator's triggering operation on the production stop mode control button.

[0091] In an optional embodiment, when a trigger operation on a shutdown mode control button is received, the belt-type pellet roasting system is controlled to enter the shutdown mode through the shutdown mode control button.

[0092] In the embodiments of the present application, on the one hand, through the continuous collection and analysis of operating data, real-time monitoring and early warning of the equipment status can be achieved; the target detection results not only include whether an abnormality occurs, but also accurately locate the abnormal location, identify the abnormal type and evaluate the abnormal level, so that the problem can be quickly and accurately identified and handled in a timely manner; on the other hand, compared with manual judgment and intervention, through automated detection and control, it is possible to respond in the shortest time, minimize the fault repair time and the cycle of restoring normal production. In addition, the use of corresponding control modes according to different abnormality levels can ensure that even in the event of partial equipment failure, the entire production line can still maintain a high degree of stability and continuity. For example, minor abnormalities can be overcome through local adjustments, while major failures trigger a comprehensive emergency plan.

[0093] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0094] Based on the same inventive concept, embodiments of the present application also provide a device for handling belt-type pellet roasting anomalies, for implementing the aforementioned method for handling belt-type pellet roasting anomalies. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for handling belt-type pellet roasting anomalies provided below can be found in the aforementioned definition of the method for handling belt-type pellet roasting anomalies, and will not be further elaborated here.

[0095] In one embodiment, Figure 5 As shown, a belt-type pellet roasting abnormality treatment device is provided, the device comprising: An acquisition module 10 is used to acquire operating data in the belt pellet roasting system; The detection module 20 is configured to detect the safety status of the belt-type pellet roasting system based on the operation data through a first detection algorithm and / or a second detection algorithm to obtain a target detection result; wherein the target detection result includes at least one of whether there is an abnormality, abnormality location, abnormality type and abnormality level; the detection of the safety status of the belt-type pellet roasting system based on the operation data through the first detection algorithm and / or the second detection algorithm to obtain the target detection result includes: determining the static safety factor of each component in the belt-type pellet roasting system according to the theoretical life value and service life value of each component; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining the first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operation data into a target detection model to obtain a second detection result; and determining the target detection result according to the first detection result and / or the second detection result; The control module 30 is configured to control the belt pellet roasting system according to a control mode matching the abnormality level when the target detection result indicates that the belt pellet roasting system is abnormal.

[0096] In one embodiment, the structure of the target detection model includes an input end, a backbone network, a neck network and a prediction end.

[0097] In one embodiment, the detection module 20 is configured to perform the following steps: determining a rate of change of the firing parameter based on a measured value and a reference value of the firing parameter of the component; The safety assessment value of each component is determined, and the dynamic safety factor is determined based on the firing parameter change rate of each component and the corresponding safety assessment value.

[0098] In one embodiment, the control module 30 is configured to perform the following steps: In the case where the abnormality level is a first-level response, a corresponding compensation control mode is determined according to the abnormality type; wherein the first-level response indicates that the belt pellet roasting system has an operational abnormality; According to the compensation control mode, the roasting parameters corresponding to the abnormal type are adjusted until the production requirements are met.

[0099] In one embodiment, the belt-type pellet roasting system includes at least a green ball transport subsystem, a roasting subsystem, and a combustion-supporting subsystem; the roasting subsystem includes a roasting assembly; the combustion-supporting subsystem includes a combustion-supporting blower and a burner; the control module 30 is used to perform the following steps: When the abnormality level is a secondary response, the roasting parameters of specific components in the belt pellet roasting system are adjusted according to the low fire mode until the setting conditions corresponding to the low fire mode are met; wherein, the secondary response indicates that there is a mechanical abnormality in the belt pellet roasting system; the setting conditions include that the temperature parameter of the roasting component is less than a first threshold, the operating speed of the roasting component is less than a second threshold, the operating frequency of the combustion-supporting fan is less than a third threshold and / or the green pellet transmission subsystem is in a shutdown state.

[0100] In one embodiment, the control module 30 is configured to perform the following steps: When the abnormality level is level three, an emergency sequential shutdown strategy is established based on the abnormality location and production process; wherein, the level three response indicates that the safety risk of the belt pellet roasting system is greater than the warning level; According to the emergency sequential shutdown strategy, the belt pellet roasting system is controlled to enter a shutdown state.

[0101] In one embodiment, the belt-type pellet roasting system includes a low-fire mode control button and a shutdown mode control button; the device further includes at least one of the following: The control module 30 is configured to control the belt-type pellet roasting system to enter a low fire mode via the low fire mode control button when a trigger operation is received on the low fire mode control button; The control module 30 is configured to control the belt-type pellet roasting system to enter a shutdown mode via the shutdown mode control button when a trigger operation on the shutdown mode control button is received.

[0102] Each module in the above-mentioned belt pellet roasting abnormality handling device can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor of the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

[0103] In one embodiment, an electronic device is provided, whose internal structure diagram can be as follows: Figure 6As shown. The electronic device includes a processor, memory, a communication interface, a display unit, and an input device connected via a method bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating method and a computer program. The internal memory provides an environment for the operation of the operating method and computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal via wired or wireless communication. The wireless communication method can be achieved through Wi-Fi, a mobile cellular network, NFC (near field communication), or other technologies. When executed by the processor, the computer program implements an image processing method. The display screen of the electronic device can be a liquid crystal display or an electronic ink display screen. The input device of the electronic device can be a touch layer covering the display screen, or keys, a trackball, or a touchpad provided on the electronic device housing, or an external keyboard, touchpad, or mouse.

[0104] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the electronic device to which the solution of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0105] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0106] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps performed by a processor of an electronic device when the computer program is executed by a processor.

[0107] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0108] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), compilable logic units, data processing logic units based on quantum computing, and the like.

[0109] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A belt pellet roasting abnormality treatment method, characterized in that: The method comprises: Obtain operating data in the belt pellet roasting system; Based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result; wherein, the target detection result includes at least one of whether there is an abnormality, abnormality location, abnormality type and abnormality level; based on the operating data, the safety status of the belt pellet roasting system is detected by the first detection algorithm and / or the second detection algorithm to obtain a target detection result, including: determining the static safety factor of the component according to the theoretical life value and service life value of each component in the belt pellet roasting system; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operating data into the target detection model to obtain a second detection result; determining the target detection result according to the first detection result and / or the second detection result; When the target detection result indicates that an abnormality occurs in the belt-type pellet roasting system, the belt-type pellet roasting system is controlled according to a control mode that matches the abnormality level.

2. The method according to claim 1, characterized in that The structure of the target detection model includes an input end, a backbone network, a neck network and a prediction end.

3. The method according to claim 1, characterized in that Determining the dynamic safety factor based on the rate of change of the roasting parameters of each component includes: determining a rate of change of the firing parameter based on a measured value and a reference value of the firing parameter of the component; The safety assessment value of each component is determined, and the dynamic safety factor is determined based on the firing parameter change rate of each component and the corresponding safety assessment value.

4. The method according to claim 1, wherein The controlling of the belt pellet roasting system according to the control mode matching the abnormality level includes: In the case where the abnormality level is a first-level response, a corresponding compensation control mode is determined according to the abnormality type; wherein the first-level response indicates that the belt pellet roasting system has an operational abnormality; According to the compensation control mode, the roasting parameters corresponding to the abnormal type are adjusted until the production requirements are met.

5. The method according to claim 1, wherein The belt-type pellet roasting system comprises at least a green pellet transport subsystem, a roasting subsystem, and a combustion-supporting subsystem; the roasting subsystem comprises a roasting assembly; the combustion-supporting subsystem comprises a combustion-supporting blower and a burner; and controlling the belt-type pellet roasting system according to a control mode matching the abnormality level comprises: When the abnormality level is a secondary response, the roasting parameters of specific components in the belt pellet roasting system are adjusted according to the low fire mode until the setting conditions corresponding to the low fire mode are met; wherein, the secondary response indicates that there is a mechanical abnormality in the belt pellet roasting system; the setting conditions include that the temperature parameter of the roasting component is less than a first threshold, the operating speed of the roasting component is less than a second threshold, the operating frequency of the combustion-supporting fan is less than a third threshold and / or the green pellet transmission subsystem is in a shutdown state.

6. The method according to claim 1, wherein The controlling of the belt pellet roasting system according to the control mode matching the abnormality level includes: When the abnormality level is level three, an emergency sequential shutdown strategy is established based on the abnormality location and production process; wherein, the level three response indicates that the safety risk of the belt pellet roasting system is greater than the warning level; According to the emergency sequential shutdown strategy, the belt pellet roasting system is controlled to enter a shutdown state.

7. The method according to claim 1, characterized in that The belt-type pellet roasting system includes a low-fire mode control button and a shutdown mode control button; the method further includes at least one of the following: When a trigger operation on the low fire mode control button is received, the belt-type pellet roasting system is controlled to enter the low fire mode through the low fire mode control button; When a trigger operation on the shutdown mode control button is received, the belt-type pellet roasting system is controlled to enter the shutdown mode through the shutdown mode control button.

8. A belt-type pellet roasting abnormality treatment device, characterized in that: The device comprises: An acquisition module is used to obtain operating data in the belt pellet roasting system; A detection module is configured to detect the safety status of the belt-type pellet roasting system based on the operation data through a first detection algorithm and / or a second detection algorithm to obtain a target detection result; wherein the target detection result includes at least one of whether there is an abnormality, abnormality location, abnormality type and abnormality level; the detection of the safety status of the belt-type pellet roasting system based on the operation data through the first detection algorithm and / or the second detection algorithm to obtain a target detection result includes: determining the static safety factor of each component in the belt-type pellet roasting system according to the theoretical life value and service life value of each component; determining the dynamic safety factor according to the roasting parameter change rate of each component; determining the reference safety factor according to the abnormal duration of the abnormal signal generated by each component; obtaining a first detection result according to the static safety factor, the dynamic safety factor and / or the reference safety factor; inputting the operation data into a target detection model to obtain a second detection result; determining the target detection result according to the first detection result and / or the second detection result; The control module is configured to control the belt pellet roasting system according to a control mode matching the abnormality level when the target detection result indicates that the belt pellet roasting system is abnormal.

9. An electronic device, characterized in that: The method comprises a processor and a memory for storing a computer program of the processor; wherein the processor is configured to implement the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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