An automated chute thermal insulation and anti-coking system, method and device

Abstract

The present invention relates to the field of furnace smelting technology, and discloses an automated chute thermal insulation and anti-coking system, method and device. The method includes arranging multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute, and the temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output; when the temperature value of a certain area of ​​the chute is lower than the critical value, the heating elements of two adjacent parts of the certain area are started and heated; the flow rate of the high-temperature melt in the chute is obtained, and it is determined whether the area in the chute has coked, and the coordinates of the area where coking has occurred are sent to the intelligent feedback component; the coked area is decoked by an automatic decoking device. The system includes a temperature monitoring component, a heating and insulation component, a coking visual monitoring component, a coking automatic removal component and an intelligent feedback component. The present invention realizes the automation and intelligence of chute anti-coking; no manual decoking operation is required.

Description

Technical Field

[0001] The present invention relates to the technical field of furnace smelting, and in particular to an automated chute heat preservation and anti-coking system, method and device. Background Art

[0002] Furnace smelting, high-temperature furnaces, and chutes are crucial components of the metallurgical and smelting processes, each playing a specific role in the overall smelting process. Furnace smelting is the extraction and processing of metals or alloys in a high-temperature furnace. The high-temperature furnace is the interior of the furnace, primarily used for heating and smelting materials. The chute is a channel or structure used to guide molten metal, slag, or gas during the smelting process. Typically located at the bottom or side of the furnace, it effectively directs the smelted products to the next processing step or collection. The chute operates in the lower part of the high-temperature furnace, at temperatures of approximately 1000°C. The high-temperature melt easily forms a large amount of coke on the chute, which can cause blockage and seriously affect the normal operation of the furnace smelting process. In order to maintain the normal operation of the chute, operators need to go to the site to observe the coking condition of the chute and use a long steel chisel to poke the chute into the coke removal manually at regular intervals. The chute under the furnace is in a high temperature state. Due to the unstable negative pressure inside, the high-temperature molten material may splash out at any time. Even if the operators wear protective clothing during the coke removal process, scalding accidents may occur from time to time. Therefore, an automated chute insulation and anti-coking system is urgently needed to replace manual coke removal, avoid scalding accidents caused by high temperature environments, and ensure the safe and stable operation of the chute.

[0003] Prior art one, Chinese patent, application number: 202110617321.6 discloses an online detection device and method for the FeO content of sintered ore with an inclined sleeve structure, including an electronic control system, a feeding and batching scale, a feeding chute arranged below the drop point of the feeding and batching scale, a magnetic induction coil and its frame sleeved on the outer wall of the middle part of the feeding chute, a material level detection instrument arranged above the feeding chute, and a material flow detection instrument arranged below the feeding chute. The feeding chute includes a No. 1 chute and a No. 2 chute corresponding to the No. 1 chute. Although the blocking state can be automatically determined and the feeding is stopped at the same time to avoid material piling; the feeding chute and the magnetic induction coil and its frame are lubricated and installed with a sleeve structure, which is convenient for extracting and reinstalling the feeding chute from the magnetic induction coil and its frame. The feeding chute adopts a detachable split structure, which can easily remove the blocked material and reduce the labor intensity of maintenance personnel. However, cleaning coke in a high-temperature environment can easily cause burns, and the efficiency of coke cleaning mostly depends on the experience of the personnel, resulting in poor coke cleaning results.

[0004] Prior art two, Chinese patent, application number: 202110617320.1 discloses an online detection device and method for the FeO content of sintered ore that is convenient for cleaning blockages, including an electronic control system, a feeding and batching scale, a feeding chute arranged below the drop point of the feeding and batching scale, a magnetic induction coil and its frame sleeved on the lower outer wall of the feeding chute, a material level detection instrument arranged above the feeding chute, and a material flow detection instrument arranged below the feeding chute. Although the blockage state is automatically judged and the feeding is stopped at the same time to avoid material pile-up; the feeding chute and the magnetic induction coil and its frame are lubricated and installed with a sleeve structure, which is convenient for extracting and reinstalling the feeding chute from the magnetic induction coil and its frame, reducing the labor intensity of maintenance personnel; avoiding the wear of the magnetic induction coil and the frame, improving the service life of the equipment, and reducing the maintenance amount and operating cost of the measuring device. However, the coke cleaning efficiency is still not high, and it is easy to cause safety accidents.

[0005] Prior art three, Chinese patent application number: 202311187862.5, discloses a method for determining flux residue in aluminum alloy melt, comprising the following steps: adding a refining agent to the aluminum melt during the smelting and refining stage of the cast aluminum alloy; wherein the smelting temperature is controlled at 720-770°C and the refining temperature is controlled at 700-750°C; during refining, adding a refining agent and introducing an inert gas; transferring the aluminum alloy liquid from the smelting furnace to a standing furnace, then from the standing furnace to a chute, passing through an online melt purification system, and reaching a transfer sleeve at the end of the chute; during the aluminum alloy liquid casting stage, the aluminum alloy liquid flows downward from the end of the chute into the transfer sleeve; and determining the presence of flux residue by measuring the aluminum liquid injection velocity in the transfer sleeve. Although by pre-determining whether the flux has residual components in the early stage of production, it is ultimately confirmed whether the refining agent is suitable for aluminum alloy melt processing applications, providing support and guarantee for the suitability of different fluxes for aluminum alloy melting and casting processes. However, there is a lack of technical means to detect coking in the chute, and coke removal still needs to be done manually, which is not only inefficient but also prone to causing injuries.

[0006] Currently, the coke cleaning process in the existing technologies 1, 2 and 3 is complicated, time-consuming and labor-intensive, and prone to burn accidents, resulting in poor safety of the coke cleaning process. Therefore, the present invention provides an automated chute heat preservation and anti-coking system, method and device. Summary of the Invention

[0007] The main purpose of the present invention is to provide an automated chute insulation and anti-coking system, method and device to solve the problem in the prior art that the coke cleaning process is cumbersome, time-consuming and labor-intensive, prone to scalding accidents, and leads to poor safety of coke cleaning work.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] An automated chute heat preservation and anti-coking system, comprising:

[0010] A temperature monitoring component is used to arrange multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute. The temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output;

[0011] The heating and insulation component is used to start heating elements in two adjacent parts of a certain area under the control of the intelligent feedback component when the temperature value of a certain area of ​​the chute is lower than the critical value;

[0012] The coking visual monitoring component is used to obtain the flow rate of the high-temperature melt in the chute, determine whether coking occurs in an area within the chute, and send the coordinates of the coking area to the intelligent feedback component;

[0013] An automatic coke removal component is used to clear the coked area through an automatic coke removal device under the control of an intelligent feedback component;

[0014] The intelligent feedback component is used to control the temperature monitoring component, the heating and insulation component, the coke visual monitoring component and the coke automatic removal component, and receive data fed back by the temperature monitoring component, the heating and insulation component, the coke visual monitoring component and the coke automatic removal component; and when coke is detected in the chute, the heating and insulation component maintains the heating state, and the coke automatic removal component starts to perform coke clearing through the position provided by the coke visual monitoring component.

[0015] As a further improvement of the present invention, the temperature monitoring component includes:

[0016] The signal acquisition module is used for temperature acquisition equipment to directly contact the chute wall through the adjacent thermocouple or thermal resistance sensor to obtain actual temperature information; the detected temperature information is converted into an analog voltage signal proportional to the temperature; the analog voltage signal is amplified, filtered and linearized to obtain a conditioned analog voltage signal;

[0017] The analog-to-digital conversion module is used to input the conditioned analog signal into the analog-to-digital converter and quantize the analog voltage value of each sample into a corresponding digital value; the converted digital signal is smoothed by the digital signal processor;

[0018] The signal output module is used to output the temperature value after digital signal processing through the interface for processing and judgment by the intelligent feedback component.

[0019] As a further improvement of the present invention, the heating and heat preservation component includes:

[0020] The element layout module is used to set up multiple areas inside the chute, each area is equipped with a heating element to achieve local heating;

[0021] Zone heating module, which is used to install heating elements in the refractory layer outside the chute wall to form a circular heating zone; multiple heating zones are arranged outside the chute to form a preliminary heating grid;

[0022] The numerical comparison module is used to monitor the output of the temperature acquisition device in real time. When the temperature of a certain area is lower than the set critical value, it responds; it automatically adjusts the adjacent heating elements to turn on and stops heating when the final temperature is higher than the critical value.

[0023] As a further improvement of the present invention, the coking visual monitoring component includes:

[0024] A data processing module is used to obtain three-dimensional point cloud data and three-dimensional coordinate data of the flow image of the high-temperature melt in the chute through a scanning device. The three-dimensional point cloud data is used to capture the dynamic shape and flow characteristics of the melt. The flow image is preprocessed, including filtering, to obtain preprocessed three-dimensional point cloud data;

[0025] The flow change module is used to correct the 3D point cloud data through point cloud deformation analysis, extract the 3D characteristics and volume information of the melt, calculate the material mass flow rate per unit time, and monitor the changes in mass flow rate;

[0026] The coking judgment module is used to determine that coking may occur in the current area when the monitored flow rate has obvious fluctuations and reaches the set threshold, and transmit the location information to the intelligent feedback component for processing.

[0027] As a further improvement of the present invention, the automatic coking removal component includes:

[0028] The travel and positioning module is used to control the movement of the automatic decoking device, including the movement of the travel track and the position adjustment of the transverse moving tube; it is used to perform positioning when the laser scanning camera detects coking;

[0029] The coke clearing arm and drive module is used to extend and retract the coke clearing arm and move the coke clearing device to the coke accumulation area in the chute to complete the coke clearing operation. It contains multiple drive mechanisms that automatically align with the coke accumulation area and perform coke clearing upon receiving signals from the intelligent feedback system.

[0030] The coke clearing operation module is used to utilize the provided coke clearing equipment to thaw, rub and collide the coked materials, and to make them fall off from the chute wall through the centrifugal force generated by the rotating coke clearing hammer.

[0031] As a further improvement of the present invention, the intelligent feedback component includes:

[0032] A data receiving and processing module is used to receive feedback data from the temperature monitoring component, the coking visual monitoring component and the coking automatic removal component, including temperature values, flow information and coking locations;

[0033] The control and regulation module is used to control the heating elements of the heating and insulation components based on the monitored temperature and coking status. The intelligent feedback component starts heating when needed to maintain the temperature of the chute within an appropriate range. It also starts the relevant operations of the automatic coking removal component. When the coking visual monitoring component detects the occurrence of coking, it directs the coking cleaning equipment to automatically remove coking.

[0034] The decision-making function module is used to perform intelligent analysis, make corresponding decisions, and adjust the defocusing frequency under different operating conditions.

[0035] To achieve the above object, the present invention also provides the following technical solutions:

[0036] An automated chute heat preservation and anti-coking method, which is applied to the automated chute heat preservation and anti-coking system, comprises:

[0037] Multiple temperature acquisition devices are arranged in the grooves of the refractory material layer on the back of the chute. The temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output;

[0038] When the temperature value of a certain area of ​​the chute is lower than the critical value, the heating elements of two adjacent parts of the area are activated to heat;

[0039] The flow rate of the high-temperature melt in the chute is obtained to determine whether coking occurs in an area within the chute and obtain the coordinates of the area where coking occurs; the coked area is decoked using an automatic decoking device.

[0040] As a further improvement of the present invention, the method of starting the heating elements of two adjacent parts of a certain area includes:

[0041] Temperature acquisition devices are installed at multiple locations within the chute to monitor the temperature of different areas in real time. The temperature acquisition devices continuously acquire temperature data of the melt material within the chute and feed it back to the intelligent feedback system. The intelligent feedback component sets a critical value t based on the characteristics of the melt material to determine whether there is a coking risk. When the temperature displayed by the temperature acquisition device in a certain area is lower than the critical value t, the current area is determined to have a potential coking risk.

[0042] The intelligent feedback component controls two adjacent heating elements to start heating. The heating elements are installed in the refractory material outside the chute wall and provide heat to the heating area through a circular path. After the heating elements are working, the temperature gradually rises until the temperature detected by the temperature acquisition device is 10° higher than the critical value t, that is, when it reaches t+10°, the heating stops.

[0043] In the conveying direction of the chute, a layer of heating elements is arranged every h times, staggered with the temperature collection equipment; from the bottom of the kiln to the next kiln, m layers of heating elements are arranged along the chute to ensure uniform temperature and form multi-layer heating from bottom to top; during the heating process, the temperature collection equipment continuously obtains data, and the intelligent feedback component detects the temperature changes in each area in real time; if the monitored temperature drops below the critical value t again, the heating process of the two adjacent parts of the heating elements is repeated.

[0044] As a further improvement of the present invention, determining whether coking occurs in an area within the chute includes:

[0045] A belt conveyor is built parallel to the chute, and a laser scanning camera is placed on the upper end of one side. Laser scanning is used to obtain the flow of high-temperature melt in the conveyor chute, generate three-dimensional coordinate data, and apply a filtering algorithm to process the image to remove interference.

[0046] The acquired 3D coordinate data from laser scanning is analyzed, and point cloud deformation analysis technology is used to correct the data to extract the 3D characteristics and volume information of the melt. The measured melt volume is converted into the mass flow rate of the material through formula calculation.

[0047] The monitored material flow data is input into the intelligent feedback control component to optimize the material delivery plan and grasp the flow changes in real time; based on the monitoring results, the equipment control parameters are adjusted, the data collection frequency is optimized, and the alarm threshold is set; when high flow is detected, the frequency of laser scanning is increased.

[0048] To achieve the above object, the present invention also provides the following technical solutions:

[0049] An automated chute heat preservation and anti-coking device, which is applied to the automated chute heat preservation and anti-coking method, the automated chute heat preservation and anti-coking device comprising: a high-temperature wireless temperature sensor, a heating element, a laser scanning camera, and a coke clearing device;

[0050] Among them, high-temperature wireless temperature sensors, heating elements, laser scanning cameras and defocusing equipment are connected to the intelligent feedback component;

[0051] The high-temperature wireless temperature sensor is embedded in the refractory layer. The inner side of the refractory layer is a chute, and the inside of the chute is a high-temperature melt.

[0052] The heating element is embedded in the refractory layer and arranged in the conveying direction of the chute, with the high-temperature wireless temperature sensor interposed between them;

[0053] A belt conveyor is built parallel to the chute, and a laser scanning camera is placed on the upper end of one side of the belt conveyor to obtain the flow conditions of the high-temperature melt in the conveying chute through laser scanning;

[0054] The decoking equipment is placed above the chute, at a height lower than the laser scanning camera. It consists of a travel track, a transverse moving tube, a decoking arm, and a decoking device. The decoking arm can be freely extended and retracted to ensure that it can be moved to various positions in the chute. Driven by an intelligent feedback component, it starts working when the laser scanning camera detects the coking situation and provides its specific location information.

[0055] The temperature monitoring component of the present invention monitors the temperature of the chute wall in real time by arranging multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute; the temperature acquisition device converts the measured analog signal into a digital signal and outputs it to ensure data accuracy. Significance: Real-time temperature monitoring can effectively prevent the melt from solidifying due to excessively low temperature, thereby reducing the occurrence of coking; temperature data provides an important basis for subsequent heating and cleaning measures, ensuring that the system operates within a safe and efficient temperature range. When the temperature of a certain area of ​​the chute is lower than the critical value, the heating and insulation component can automatically start the heating elements of the two adjacent parts for heating to maintain a suitable temperature. Significance: Keep the temperature of the chute within the set range to prevent the high-temperature melt from coking due to temperature reduction; the automation of heating measures reduces the need for manual intervention and improves the operational stability and safety of the system. The coking visual monitoring component monitors the flow of high-temperature melt in the chute and determines whether coking occurs; once coking is found, the coordinate information of the coking area can be obtained and transmitted to the intelligent feedback component in a timely manner. Significance: Through real-time monitoring, early signals of coking can be effectively captured, and timely measures can be taken to deal with them, reducing interference with the production process; improving the understanding of the coking situation and providing accurate data support for coking removal. After receiving instructions from the intelligent feedback component, the automatic coking removal component can start the automatic coking device to clean the area where coking has occurred. Significance: Automated coking operations reduce manual intervention and secondary safety risks for workers, and improve the efficiency and accuracy of coking; coking removal not only ensures the smooth flow of the chute, greatly improves the working efficiency of the system, but also extends the service life of the equipment. The intelligent feedback component coordinates the work of each sub-component, receives data feedback from each component, and issues corresponding instructions when coking is detected. Significance: Improve the overall intelligence level of the system, ensure the close coordination of temperature monitoring, heating, coking monitoring and removal processes, and form a complete closed-loop control system; through real-time data analysis and feedback, it helps to optimize operating conditions and ensure efficient and safe work in the dissolution tank. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a schematic diagram of the functional modules of an embodiment of the automated chute heat preservation and anti-coking system of the present invention;

[0057] Figure 2 This is a schematic flow chart of the steps of an embodiment of the automated chute heat preservation and anti-coking method of the present invention;

[0058] Figure 3 This is a flow chart of the steps of converting analog signals into digital signal outputs in one embodiment of the automated chute heat preservation and anti-coking method of the present invention;

[0059] Figure 4 This is a schematic diagram of the layout of temperature acquisition equipment in one embodiment of the automated chute heat preservation and anti-coking method of the present invention;

[0060] Figure 5 This is a schematic flow chart of the steps for activating heating elements in two adjacent parts of a certain area according to one embodiment of the automated chute heat preservation and coking prevention method of the present invention;

[0061] Figure 6 This is a schematic diagram of the layout of heating elements in one embodiment of the automated chute heat preservation and anti-coking method of the present invention;

[0062] Figure 7 This is a flow chart showing the steps of determining whether coking occurs in an area within a chute according to an embodiment of the automated chute heat preservation and coking prevention method of the present invention;

[0063] Figure 8 This is a functional module diagram of a high-temperature wireless temperature sensor of an embodiment of an automated chute heat preservation and anti-coking device of the present invention;

[0064] Figure 9 This is a functional module diagram of a heating element of an embodiment of an automated chute heat preservation and anti-coking device of the present invention;

[0065] Figure 10 This is a schematic diagram of the functional modules of a laser scanning camera in one embodiment of the automated chute heat preservation and anti-coking device of the present invention;

[0066] Figure 11 This is a functional module diagram of a coke cleaning device according to an embodiment of the automated chute heat preservation and anti-coking device of the present invention;

[0067] Figure 12 This is a schematic structural diagram of an embodiment of an electronic device of the present invention;

[0068] Figure 13 This is a schematic structural diagram of an embodiment of a storage medium of the present invention. DETAILED DESCRIPTION

[0069] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0070] The terms "first", "second" and "third" in the present invention are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first", "second" and "third" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "multiple" is at least two, for example, two, three, etc., unless otherwise clearly and specifically defined. All directional indications in the embodiments of the present invention (such as up, down, left, right, front, back...) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0071] References herein to "embodiments" 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 invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate 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.

[0072] like Figure 1 As shown, this embodiment provides an embodiment of an automated chute heat preservation and anti-coking system. In this embodiment, the automated chute heat preservation and anti-coking system includes a temperature monitoring component 1, a heating and heat preservation component 2, a coking visual monitoring component 3, a coking automatic removal component 4, and an intelligent feedback component 5, which are electrically connected in sequence.

[0073] Among them, the temperature monitoring component 1 is used to arrange multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute. The temperature acquisition equipment is used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output; the heating and heat preservation component 2 is used to start the heating elements of two adjacent parts of a certain area under the control of the intelligent feedback component 5 when the temperature value of a certain area of ​​the chute is lower than the critical value, and heat them; the coking visual monitoring component 3 is used to obtain the flow rate of the high-temperature melt in the chute, determine whether coking occurs in the area inside the chute, and send the coordinates of the area where coking occurs to the intelligent feedback component 5. Feedback component 5; the automatic coke removal component 4 is used to clear the coked area through the automatic coke clearing device under the control of the intelligent feedback component 5; the intelligent feedback component 5 is used to control the temperature monitoring component 1, the heating and insulation component 2, the coke visual monitoring component 3 and the automatic coke removal component 4, and receive the data fed back by the temperature monitoring component 1, the heating and insulation component 2, the coke visual monitoring component 3 and the automatic coke removal component 4; and when coke is detected in the chute, the heating and insulation component 2 is allowed to maintain the heating state, and the automatic coke removal component 4 starts to perform the coke clearing behavior through the position provided by the coke visual monitoring component 3.

[0074] Preferably, the temperature monitoring component 1 of this embodiment monitors the temperature of the chute wall in real time by arranging multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute; the temperature acquisition device converts the measured analog signal into a digital signal and outputs it to ensure data accuracy. Significance: Real-time temperature monitoring can effectively prevent the melt from solidifying due to excessively low temperature, thereby reducing the occurrence of coking; temperature data provides an important basis for subsequent heating and removal measures, ensuring that the system operates within a safe and efficient temperature range. Heating and insulation component 2 When the temperature of a certain area of ​​the chute is lower than the critical value, the component can automatically start the heating elements of the two adjacent parts for heating to maintain a suitable temperature. Significance: Keep the temperature of the chute within the set range to prevent the high-temperature melt from coking due to temperature reduction; the automation of heating measures reduces the need for manual intervention and improves the operational stability and safety of the system. The coking visual monitoring component 3 monitors the flow of the high-temperature melt in the chute and determines whether coking occurs; once coking is found, the coordinate information of the coking area can be obtained and transmitted to the intelligent feedback component in a timely manner. Significance: Through real-time monitoring, early signals of coking can be effectively captured, and timely measures can be taken to deal with them, reducing interference with the production process; improving the understanding of the coking situation and providing accurate data support for coking removal. After receiving instructions from the intelligent feedback component 5, the automatic coking removal component 4 can start the automatic coking device to clean the area where coking has occurred. Significance: The automated coking operation reduces manual intervention and secondary safety risks for workers, and improves the efficiency and accuracy of coking; coking removal not only ensures the smooth flow of the chute, greatly improves the working efficiency of the system, but also extends the service life of the equipment. The intelligent feedback component 5 coordinates the work of each sub-component, receives data feedback from each component, and issues corresponding instructions when coking is detected. Significance: Improve the overall intelligence level of the system, ensure the close coordination of temperature monitoring, heating, coking monitoring and removal processes, and form a complete closed-loop control system; through real-time data analysis and feedback, it helps to optimize operating conditions and ensure efficient and safe work in the dissolution tank.

[0075] In summary, the mutual cooperation of the various components of this embodiment in the system forms a complete automated and intelligent thermal insulation and anti-coking solution. It helps to: reduce the number of manual interventions and effectively reduce human errors; improve the reliability and stability of materials during the smelting process and ensure production safety; optimize resource consumption through real-time monitoring and feedback, that is, improve smelting efficiency and reduce energy consumption; significantly reduce the negative impact of coking on the production process and ensure smooth material transportation. It makes the smelting process more scientific, efficient and automatic, and lays a solid foundation for the intelligent development of the modern metallurgical industry. This embodiment realizes the automation and intelligence of chute anti-coking; there is no need for manual coke cleaning operations, which avoids scalding accidents caused by high temperature environments, and is an automated chute thermal insulation and anti-coking system that improves the efficiency, safety, energy saving and environmental protection of the furnace as a whole.

[0076] Furthermore, the temperature monitoring component 1 specifically includes:

[0077] The signal acquisition module is used for temperature acquisition equipment to directly contact the chute wall through the adjacent thermocouple or thermal resistance sensor to obtain actual temperature information; the detected temperature information is converted into an analog voltage signal proportional to the temperature; the analog voltage signal is amplified, filtered and linearized to obtain a conditioned analog voltage signal;

[0078] The analog-to-digital conversion module is used to input the conditioned analog signal into the analog-to-digital converter and quantize the analog voltage value of each sample into a corresponding digital value; the converted digital signal passes through the digital signal processor for smoothing and filtering;

[0079] Among them, the expression for improving the efficiency of the analog-to-digital converter is:

[0080] Setting multiple parameters that affect the efficiency of the analog-to-digital converter: F s represents the sampling frequency, ENOB represents the effective number of bits, V ref Indicates the reference voltage, T conv Indicates the conversion time, P total Indicates total power consumption, BW indicates signal bandwidth;

[0081] Comprehensive performance matrix, construct input parameter matrix X and impact matrix A:

[0082] X=[F s ENOB V ref T conv P total BW]

[0083]

[0084] where each k ij Indicates the interaction between different parameters.

[0085] Nonlinear correction term, in order to make the equation include nonlinear effects, a nonlinear correction term Φ can be introduced:

[0086]

[0087] Among them, (α, β, γ) are the influence coefficients, and (n, m, p, q, r, s) are the exponents of each variable, reflecting the nonlinear effects of each parameter;

[0088] Combining the above matrix with the nonlinear correction term, the final analog-to-digital converter efficiency expression is:

[0089]

[0090] Where P = A·X;

[0091] The expression demonstrates that the efficiency of an analog-to-digital converter is a comprehensive expression of the linear combination of input parameters and their nonlinear effects. It not only considers the linear combination of different parameter configurations but also introduces the complex interactions and nonlinear characteristics between the parameters, making this expression more explanatory and practical in practical applications.

[0092] The signal output module is used to output the temperature value after digital signal processing through the interface for processing and judgment by the intelligent feedback component 5.

[0093] Preferably, the signal acquisition module of this embodiment directly contacts the chute wall using a thermocouple or thermistor sensor to accurately acquire the actual temperature. The measured temperature information is converted into an analog voltage signal proportional to the temperature. The analog signal is amplified, filtered, and linearized to ensure signal quality for subsequent processing. Significance: Direct measurement and processing minimizes measurement error and improves the system's response accuracy. The conditioned signal effectively removes noise, enhances system stability, and provides a reliable input for subsequent digital conversion. The analog-to-digital conversion module converts the conditioned analog signal into a digital signal using an analog-to-digital converter for digital processing. The converted digital signal is smoothed and filtered by a digital signal processor to remove transient fluctuations and high-frequency noise. Significance: The digital signal easily interacts with modern computers and digital instruments, laying the foundation for subsequent data analysis and processing. Efficient digital processing enables more real-time temperature monitoring and faster adaptation to environmental changes. Nonlinear correction and comprehensive performance: By constructing a performance matrix and nonlinear correction terms, the overall efficiency of the analog-to-digital converter is evaluated, including consideration of the interactions of multiple variables. This allows the system to adjust in real time to varying operating conditions to improve overall conversion efficiency. Significance achieved: The introduction of nonlinear correction terms can more realistically reflect the conversion efficiency of the sensor under different working conditions and avoid the limitations of a single expected value; through a comprehensive understanding of the performance of the analog-to-digital converter, the design scheme can be optimized based on actual data. The temperature value of the signal output module after digital signal processing is output through the interface, supporting the intelligent feedback component for automatic processing and judgment; the output data can be used for a variety of subsequent operations and decision support, such as alarm systems or system control. Significance achieved: The system can quickly provide temperature data to users or automated equipment, which helps to quickly respond to temperature changes and ensure safety and stability; the interface design allows for further integration of more complex control systems to achieve comprehensive temperature monitoring and automated management.

[0094] In summary, the temperature monitoring assembly 1 of this embodiment forms an efficient, accurate, and stable temperature monitoring system through the coordinated operation of signal acquisition, analog-to-digital conversion, comprehensive performance evaluation, and signal output. This system not only monitors temperature changes in real time but also provides a basis for decision support through digital data, thereby effectively improving the safety and reliability of the production process and ensuring steady-state operation in industrial or experimental environments.

[0095] Furthermore, the heating and heat preservation component 2 specifically includes:

[0096] The element layout module is used to set up multiple areas inside the chute, each area is equipped with a heating element to achieve local heating;

[0097] Zone heating module, which is used to install heating elements in the refractory layer outside the chute wall to form a circular heating zone; multiple heating zones are arranged outside the chute to form a preliminary heating grid;

[0098] The numerical comparison module is used to monitor the output of the temperature acquisition device in real time. When the temperature of a certain area is lower than the set critical value, it responds; it automatically adjusts the adjacent heating elements to turn on and stops heating when the final temperature is higher than the critical value.

[0099] Preferably, the element layout module of this embodiment sets up multiple areas inside the chute, and configures a heating element for each area, so as to achieve precise heating of specific areas; the heating elements are flexibly arranged according to the flow or physical properties of the melt material to form an adaptive heating scheme. The significance achieved: local heating can more effectively regulate the temperature of the melt to achieve rapid heating, reduce the overall heating time, and improve production efficiency; through targeted heating, it can effectively prevent the solidification of foreign matter or melt, reduce the possibility of coking, and ensure the fluidity and uniformity of the melt. The regional heating module installs heating elements in the refractory material layer outside the chute wall to form a surrounding heating zone to ensure the uniformity of the wall temperature; multiple heating areas are arranged outside the chute to form a preliminary heating grid structure to achieve an all-round heating effect. The significance achieved: Annular heating can effectively maintain a stable temperature of the chute wall, thereby ensuring the stability of the melt and avoiding inconsistent material quality due to uneven temperature; the various heating zones formed by Annular heating effectively reduce heat loss, improve the thermal efficiency of the entire system, and reduce energy consumption. The numerical comparison module monitors the output of the temperature acquisition device in real time and compares it with the set critical value to ensure timely response. When the temperature in a certain area falls below the set threshold, it automatically activates the adjacent heating element to ensure that the temperature quickly returns to a safe range. When the temperature rises above the critical value, heating is automatically stopped, forming an effective temperature control closed loop. The significance achieved: The combination of real-time temperature monitoring and feedback regulation improves the system's responsiveness to unexpected situations (such as temperature drops) and ensures that the temperature remains within a safe range. Through precise temperature control strategies, it can effectively prevent changes in melt properties due to temperature issues, thereby improving the quality and consistency of the final product.

[0100] In summary, this embodiment ensures precise control and management of the chute temperature, improving the overall efficiency and intelligence of the heating and insulation components. Through the combination of local heating, annular heating, and real-time monitoring, not only is precise temperature control achieved, but the risk of material failure due to uneven temperature is also reduced, ensuring the smoothness and safety of the melt processing process. Overall, the system can effectively improve production efficiency, ensure material properties, and help companies maintain stable and continuous operation during the melt material processing process.

[0101] Furthermore, the coking visual monitoring component 3 specifically includes:

[0102] A data processing module is used to obtain three-dimensional point cloud data and three-dimensional coordinate data of the flow image of the high-temperature melt in the chute through a scanning device. The three-dimensional point cloud data is used to capture the dynamic shape and flow characteristics of the melt. The flow image is pre-processed, including filtering, to obtain pre-processed three-dimensional point cloud data;

[0103] The flow change module is used to correct the 3D point cloud data through point cloud deformation analysis, extract the 3D characteristics and volume information of the melt, calculate the material mass flow rate per unit time, and monitor the changes in mass flow rate;

[0104] The coking judgment module is used to determine that coking may occur in the current area when the monitored flow rate has obvious fluctuations and reaches a set threshold, and transmit the location information to the intelligent feedback component 5 for processing.

[0105] Preferably, the data processing module of this embodiment uses a scanning device to acquire 3D point cloud data and 3D coordinate data of the flow image of the high-temperature melt in the chute. It then preprocesses the flow image, including filtering and other operations, to remove interference and noise, resulting in clearer and more accurate 3D point cloud data. This allows for high-precision capture of the dynamic morphology and flow characteristics of the melt. Preprocessing (e.g., filtering) significantly improves the quality of data used in subsequent analysis, reducing the impact of interference on the analysis results. This module provides a high-quality data foundation to ensure the accuracy of flow and state monitoring; it enables efficient data acquisition and processing, enabling rapid response to changes in the melt state. The flow change module performs point cloud deformation analysis on the 3D point cloud data, correcting the 3D data to accurately extract the 3D characteristics and volume information of the melt; it calculates the material mass flow rate per unit time and monitors changes in the mass flow rate; it provides dynamic analysis of the melt's flow characteristics, enabling the system to identify changes in the flow state; and it calculates the material mass flow rate in real time, providing quantitative indicators for subsequent monitoring and judgment. Implementation significance: By monitoring flow changes, the melt flow state can be effectively grasped and abnormal phenomena can be discovered in time; the monitoring of flow data can provide a basis for the intelligent feedback system, help control material delivery and conveying speed, and improve production efficiency. The coking judgment module monitors flow changes, and when the flow fluctuates significantly and reaches the set threshold, it determines that coking may occur in the current area; transmits the location information to the intelligent feedback component for the next step of processing; identifies coking risks early and provides a rapid feedback mechanism to avoid more serious production problems; can accurately transmit the location information of coking to subsequent systems for targeted processing. Implementation significance: Through coking judgment, the continuity and stability of the production process can be guaranteed and the occurrence of faults can be reduced; timely detection of coking and taking measures can effectively reduce the subsequent cleaning and maintenance needs, thereby reducing overall production costs.

[0106] In summary, the coking visual monitoring assembly of this embodiment constitutes a highly efficient real-time monitoring and feedback system. It not only enables precise capture and analysis of the flow state of high-temperature melts, thereby ensuring smooth production, but also provides strong support for efficient intelligent production, helping to improve overall production efficiency, reduce costs, and minimize the probability of failure. This is particularly important in modern production, helping companies maintain their competitive advantage.

[0107] Furthermore, the coke automatic removal component 4 specifically includes:

[0108] The travel and positioning module is used to control the movement of the automatic decoking device, including the movement of the travel track and the position adjustment of the transverse moving tube; it is used to perform positioning when the laser scanning camera detects coking;

[0109] The coke clearing arm and drive module is used to extend and retract the coke clearing arm and move the coke clearing device to the coke accumulation area in the chute to complete the coke clearing operation. It contains multiple drive mechanisms that automatically align with the coke accumulation area and perform coke clearing upon receiving signals from the intelligent feedback system.

[0110] The coke clearing operation module is used to utilize the provided coke clearing equipment to thaw, rub and collide the coked materials, and to make them fall off from the chute wall through the centrifugal force generated by the rotating coke clearing hammer.

[0111] Preferably, the travel and positioning module of this embodiment can effectively control the movement of the automatic decoking device on the travel track and the position adjustment on the horizontal moving tube. The precise control capability ensures that the decoking arm can accurately locate the coking area; when the laser scanning camera detects coking and transmits the position information, it can quickly start and intelligently complete the positioning operation. Implementation significance: The automated movement and positioning process reduces the need for manual intervention and can improve the efficiency and response speed of the decoking operation. Through real-time monitoring and positioning, rapid feedback and adjustments can be made, making the entire production process more intelligent and helping to shorten the fault recovery time. The decoking arm and drive device module can be freely extended and retracted to adapt to different positions and environments, ensuring that it can reach all areas that require decoking; it contains multiple drive mechanisms, so that the module can quickly and accurately align the coking area for decoking after receiving the signal. Implementation significance: It ensures that the decoking equipment can operate in complex working environments, thereby improving the comprehensiveness of decoking and reducing the occurrence of missed decoking; with the help of the automatic drive and positioning functions, it significantly reduces the dependence on operators and improves the safety and efficiency of the operation. The coke-clearing module utilizes the coke-clearing equipment to thaw, rub, and collide the coke. The centrifugal force generated by the rotating coke-clearing hammer effectively removes the coke from the chute surface. The rotation and relative motion ensure optimal friction between the hammers, improving the coke-clearing effect. Significance: Efficient coke-clearing operations can significantly reduce downtime caused by coking during production, improving production continuity. Regular coke-clearing reduces wear on equipment and reduces the incidence of failures, thereby extending equipment life and maintenance cycles.

[0112] In summary, the entire automatic coke removal component of this embodiment is designed to improve the intelligence, efficiency, and safety of the production process. Through modular design, the coordinated operation of each module not only achieves efficient coke removal, but also reduces manual intervention, improves the safety and accuracy of operations, and thus brings higher economic benefits and better operational stability to the company's production system. The automatic removal component has important application value in modern industry and can effectively improve production efficiency and product quality.

[0113] Furthermore, the intelligent feedback component 5 specifically includes:

[0114] Data receiving and processing module, used to receive feedback data from temperature monitoring component 1, coking visual monitoring component 3 and coking automatic removal component 4, including temperature value, flow information and coking location, etc.;

[0115] The control and regulation module is used to control the heating elements of the heating and heat preservation component 2 based on the monitored temperature and coking status. The intelligent feedback component 5 can start heating when needed to maintain the temperature of the chute within an appropriate range; start the relevant operations of the automatic coking removal component 4, and when the coking visual monitoring component 3 detects the occurrence of coking, it will command the coking cleaning equipment to automatically remove it;

[0116] The decision-making function module is used to perform intelligent analysis, make corresponding decisions, and adjust the defocusing frequency under different operating conditions.

[0117] Preferably, the data receiving and processing module of this embodiment can receive data from the temperature monitoring component 1, the coking visual monitoring component 3 and the coking automatic removal component 4 in real time, including temperature values, flow information and coking positions, etc., to ensure the system's dynamic understanding of the status; by preprocessing the signal, the analog signal is converted into a standardized digital signal, which is convenient for unified analysis and processing. Implementation significance: Real-time data feedback and standardized processing enhance the reliability of the data, providing an accurate basis for subsequent analysis and decision-making; data integration capabilities support the intelligent decision-making and automatic control of subsequent modules, giving the entire system a higher level of intelligence. When the control and regulation module detects that the temperature is lower than the critical value, it can quickly start the heating element of the heating and insulation component 2 to maintain the temperature of the chute within an appropriate range; in addition, it can command the coking automatic removal component 4 to start the coking operation when coking occurs; it can flexibly adjust the heating and coking strategies according to real-time data changes to ensure that the system quickly adapts to different operating conditions. Implementation significance: Through automatic temperature control and decoking operations, the need for manual intervention is reduced, and the stability and reliability of the overall system are improved; the real-time control and adjustment mechanism helps the system respond quickly to temperature and coking conditions, thereby minimizing downtime caused by coking in production and improving production efficiency. The decision-making function module performs intelligent analysis based on the collected data, generates corresponding decisions through real-time monitoring and historical data comparison, and adjusts the heating strategy or decoking frequency; using algorithms and models, it can make efficient judgments and decisions for different work scenarios. Implementation significance: Through intelligent analysis, the timing and method of heating and decoking are optimized to avoid unnecessary waste of resources and make production more economical; dynamic decision-making capabilities enable the system to better respond to changes in environmental and processing conditions, reduce the probability of coking problems, and improve product quality.

[0118] In summary, the design of the intelligent feedback component 5 of this embodiment and its modular function significantly improve the intelligence and automation level of the automated chute insulation and anti-coking system. Through real-time data collection, analysis and intelligent decision-making, the entire system can self-regulate and optimize, thereby achieving the following goals: reduce the possibility of manual intervention and erroneous operation, and ensure the safety of the production process; intelligent control and rapid response mechanisms ensure efficient and smooth production processes, and reduce downtime caused by coking; intelligent decision-making not only optimizes resource utilization, but also reduces maintenance and replacement costs caused by coking, thereby reducing overall operating costs. Through the close cooperation of its various modules, the intelligent feedback component 5 achieves high efficiency, autonomy and intelligence in the modern manufacturing process, bringing a qualitative leap in production.

[0119] like Figure 2As shown, this embodiment also provides an embodiment of an automated chute heat preservation and anti-coking method. In this embodiment, the automated chute heat preservation and anti-coking method is applied to the automated chute heat preservation and anti-coking system as in the above embodiment. The automated chute heat preservation and anti-coking method specifically includes the following steps:

[0120] Step S1: multiple temperature acquisition devices are arranged in the grooves of the refractory layer on the back of the chute. The temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output;

[0121] Step S2: When the temperature value of a certain area of ​​the chute is lower than a critical value, the heating elements of two adjacent parts of the certain area are activated to heat;

[0122] Step S3: Obtain the flow rate of the high-temperature melt in the chute, determine whether coking occurs in an area within the chute, and obtain the coordinates of the area where coking occurs; and decoke the coked area using an automatic decoking device.

[0123] Preferably, in step S1 of this embodiment, temperature acquisition is performed by arranging multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute, which can accurately and in real time measure the temperature of the chute wall area; the temperature acquisition device converts the measured analog signal into a digital signal output, and the data format is convenient for processing and analysis. Implementation significance: Continuous temperature monitoring provides important real-time data support for the entire system, enabling the system to understand and respond to temperature changes in a timely manner; the data is the basis for subsequent control and adjustment, ensuring that subsequent measures against temperature changes can make accurate and timely judgments; by arranging multiple temperature acquisition devices, redundancy can be provided, reducing the risk of single point failures and improving the overall reliability of the system. Step S2: The heating element is started. When the temperature of a certain area is detected to be lower than the set critical value, the heating element next to it is quickly started for local heating; different areas can be heated as needed to ensure that the temperature can quickly return to an appropriate range. Implementation significance: Timely heating of the temperature can effectively prevent the melt from cooling too quickly and reduce the possibility of coking; maintaining stable temperature control is conducive to the fluidity of the melt throughout the production process, improving production efficiency and stability; by precisely controlling the start-up time and area of ​​the heating element, it can effectively reduce unnecessary heat energy waste and improve energy efficiency. Step S3 flow detection and coking obtains the flow information of the high-temperature melt in the chute to provide data support for the coking status; based on the flow data, it determines whether coking occurs and accurately obtains the coordinates of the coking area; the automatic coking device can efficiently clear the determined coking area. Implementation significance: It can quickly identify and locate the coking area, ensure the timeliness and effectiveness of the coking work, and reduce the interference of coking on the production process; through regular coking, it can greatly extend the service life of the equipment, reduce the maintenance frequency, and improve the reliability of equipment operation; ensure that the melt flows smoothly and is free of coking, improve the consistency and quality of the final product, and reduce production defects caused by coking.

[0124] In summary, this embodiment forms a strict temperature monitoring and dynamic heating and anti-coking protection mechanism. The specific overall significance includes: through temperature monitoring and rapid heating response, the safety hazards caused by low temperature or coking are reduced; through effective temperature control and coking removal mechanism, the fluidity of the melt is maintained, downtime is reduced, and overall production efficiency is improved; the gradual transformation to intelligent manufacturing and the improvement of the degree of automation have an important driving effect on the optimization and upgrading of future production processes; through efficient heating, monitoring and coking removal, the costs increased by production interruptions and maintenance are reduced, thereby improving the overall economic benefits; through implementation, the coking problem of agricultural commodities or industrial materials in the production process is effectively solved, providing a strong guarantee for the stable operation and benefit growth of the enterprise.

[0125] Furthermore, if Figure 3As shown, the process of converting the analog signal into a digital signal output in step S1 specifically includes the following steps:

[0126] Step S11: The temperature acquisition device directly contacts the chute wall through an adjacent thermocouple or thermal resistance sensor to obtain actual temperature information; the detected temperature information is converted into an analog voltage signal proportional to the temperature; the analog voltage signal is amplified, filtered, and linearized to obtain a conditioned analog voltage signal;

[0127] Step S12: The conditioned analog signal enters the analog-to-digital converter, and the analog voltage value of each sample is quantized into a corresponding digital value; the converted digital signal passes through the digital signal processor for smoothing and filtering;

[0128] Step S13: The temperature value after digital signal processing is output through the interface for processing and judgment.

[0129] Preferably, in step S11 of this embodiment, temperature information is acquired and analog signal is conditioned. The temperature acquisition device directly contacts the chute wall through sensors such as thermocouples or thermal resistors, and can accurately acquire the actual temperature information of the chute. The measured temperature information will be converted into an analog voltage signal proportional to the temperature, providing a corresponding relationship between temperature and voltage. The analog voltage signal is amplified, filtered, and linearized to obtain a conditioned analog voltage signal, ensuring that the signal is stable and free from noise interference during transmission. Implementation significance: Through precise sensors and conditioning technology, the accuracy of temperature data is guaranteed, thereby laying a solid foundation for subsequent digital processing. Signal amplification and filtering can effectively reduce the interference of environmental noise, improve the validity of data, and ensure that subsequent processing can obtain reliable results. Linearization processing makes the signal output consistent in different temperature ranges, facilitating subsequent conversion and comparison, and ensuring data consistency. Step S12 performs analog-to-digital conversion and digital signal processing. The conditioned analog signal is fed into an analog-to-digital converter (ADC) to quantize the analog voltage value into a corresponding digital value, completing the signal's transition from continuous to discrete. A digital signal processor (DSP) then smoothes and filters the converted digital signal to further eliminate noise and instability in the data. Implementation significance: After converting the analog signal to a digital signal, the data can be adapted for computer processing, facilitating subsequent analysis and algorithm application. Smoothing and filtering techniques improve signal quality, reduce measurement errors, and make subsequent analysis more reliable. Digital signals are more easily interacting with modern computers and digital systems, facilitating intelligent computing and real-time data processing. Step S13 performs digital signal output and processing. The temperature value, after digital signal processing, is output through an interface for further processing and analysis by downstream systems or components. The output digital signal can be evaluated in real time by the corresponding control module of the system to determine subsequent actions, such as activating a heating element or executing other control tasks. Significance: Standardized digital output enables easy integration of temperature data with other systems or modules, improving the overall compatibility and collaboration capabilities of the system. The processed temperature digital signal provides basic data for the intelligent decision-making module, helping to make more reasonable and accurate decisions in real time, improving the system's response speed and adaptability. The integrated output data can be used for subsequent trend analysis, data recording or optimization algorithms, promoting continuous improvement of the entire system.

[0130] The layout process of the temperature acquisition equipment in this embodiment specifically includes: based on the principle of heat transfer, it can be assumed that the heat conduction process of the furnace lining is steady during the smelting process; based on the assumption, the heat conduction per unit area Q, the thermal conductivity coefficient, and the measured temperature T are known. 测 , chute wall thickness d1, refractory material layer thickness d2, sensor width d3, the actual temperature of the melt in the chute T can be calculated 实 :

[0131]

[0132] Since the temperature of the melt in different locations of the chute is often different, it is necessary to arrange multiple sensors outside the chute; the sensor arrangement requirements are:

[0133] At a specific location, n (range 3 to 5) sensors are arranged in the circumferential direction, which is a layer;

[0134] In the conveying direction, one layer is arranged every h (range 20-50 cm), from the bottom of the kiln along the chute to the next kiln, with a total of m layers;

[0135] Each layer of sensors shares a sensor host, which can display the temperature of each sensor. Figure 4 ;

[0136] The output is the temperature on each sensor, and the temperature information is transmitted to the intelligent feedback component.

[0137] In summary, this embodiment's complete process for converting analog signals into digital signals plays a crucial role in the entire temperature monitoring and control system. By accurately acquiring and converting temperature data, it ensures effective temperature monitoring and control during the production process. Signal conditioning and digital processing minimize interference and errors, enhancing the system's stability and reliability in dynamic environments. The introduction of digital signal processing drives the entire system toward intelligent development, facilitating comprehensive intelligent optimization and automatic control, and improving production efficiency and safety. The signal conversion process is not only a fundamental component of the temperature monitoring system but also provides crucial data support for higher-level intelligent analysis and decision-making, thereby promoting the modernization and efficiency of the entire manufacturing or production process.

[0138] Furthermore, if Figure 5 As shown, the process of starting the heating elements of two adjacent parts of a certain area in step S2 specifically includes the following steps:

[0139] Step S21: Temperature acquisition devices are installed at multiple locations within the chute to monitor the temperature of different areas of the chute in real time. The temperature acquisition devices continuously acquire temperature data of the melt material in the chute and feed it back to the intelligent feedback system. The intelligent feedback component sets a critical value t based on the characteristics of the melt material to determine whether there is a coking risk. When the temperature displayed by the temperature acquisition device in a certain area is lower than the critical value t, the current area is determined to have a potential coking risk.

[0140] Step S22: The intelligent feedback component controls two adjacent heating elements to start heating. The heating elements are installed in the refractory material outside the chute wall and provide heat to the circumferential heating area. After the heating elements are working, the temperature gradually rises until the temperature detected by the temperature acquisition device is 10° higher than the critical value t, that is, when it reaches t+10°, the heating stops.

[0141] Step S23: In the conveying direction of the chute, a layer of heating elements is arranged every h (range 20-50 cm), and the temperature acquisition equipment is staggered. From the bottom of the kiln to the next kiln, m layers of heating elements are arranged along the chute to ensure uniform temperature and form multi-layer heating from bottom to top. During the heating process, the temperature acquisition equipment continuously acquires data, and the intelligent feedback component detects the temperature changes in each area in real time. If the temperature is detected to fall below the critical value t again, the heating process of the two adjacent parts of the heating elements is repeated.

[0142] Preferably, in step S21 of this embodiment, temperature monitoring and risk assessment can monitor the temperature of different areas in real time by installing temperature acquisition equipment at multiple locations inside the chute; it can actively collect data and provide real-time temperature change information; the intelligent feedback component sets a critical value t according to the characteristics of the melt material, and uses it to determine whether there is a coking risk; when the temperature of a certain area is lower than the critical value, it automatically determines that the area has a potential coking risk. Implementation significance: through real-time monitoring and timely judgment, it is ensured that measures can be taken as early as possible before the coking risk occurs, thereby reducing the risk of accidents; the collection and analysis of temperature data provides a basis for subsequent decision-making, which can optimize the production process and improve production safety and efficiency. In step S22, the start-up and control of the heating element, the intelligent feedback component controls the two adjacent heating elements to start heating in order to achieve the purpose of raising the temperature; the heating element provides heat to the circumferential heating area, and the temperature gradually rises; the temperature change is continuously monitored by the temperature acquisition device to ensure that heating is stopped immediately after reaching t+10° to prevent overheating. Significance of implementation: The dynamic control of the intelligent feedback system enables the heating process to quickly respond to temperature changes, optimize heating efficiency, and avoid energy waste; preventing overheating can protect the integrity of the melt material and the chute structure, reduce maintenance costs, and extend the service life of the equipment. Step S23: Heating area layout and data feedback: In the conveying direction of the chute, a layer of heating elements is arranged every h (20-50cm) (see attached Figure 6) and are arranged in a staggered manner with temperature acquisition equipment. This layout ensures uniform coverage of the heating area and improves the heating effect; m layers of heating elements are arranged along the chute from the bottom of the kiln to the next kiln, forming an effective multi-layer heating structure. At the same time, temperature data is continuously acquired during the heating process to achieve all-round temperature monitoring. Implementation significance: A reasonable layout design helps to achieve uniform heating and prevent the coking of materials due to local low temperatures, thereby ensuring the continuity and stability of production; continuous temperature monitoring and feedback mechanisms ensure that the system can adjust the heating strategy in real time. If the monitored temperature drops to the critical value t, heating will be immediately carried out; it can effectively prevent problems caused by temperature fluctuations.

[0143] In summary, step S21 of this embodiment focuses on the accurate acquisition and judgment of data, providing a basis for subsequent appropriate measures; step S22 ensures safety and efficiency by controlling the heating process, and sets a suitable heating range to prevent overheating; step S23 ensures the uniformity of the overall heating process and the flexibility of response by optimizing the layout and continuous monitoring, thereby improving the intelligence level of the system. Through the system design and implementation of the above steps, this embodiment can achieve safe, effective and intelligent management of melt materials, reduce the risk of coking, and improve production efficiency; ensure the real-time and accuracy of temperature data; be able to automatically adjust the working status of adjacent heating elements according to temperature changes; ensure uniform heat distribution through layering and spacing design to maximize the heating effect and reduce the risk of coking; through scientific and reasonable layout and intelligent control system, the heating process in this area can effectively control the melt temperature, thereby ensuring smooth production and improving product quality.

[0144] Furthermore, if Figure 7 As shown, the process of determining whether coking occurs in the area within the chute in step S3 specifically includes the following steps:

[0145] Step S31: A belt conveyor is built parallel to the chute, and a laser scanning camera is installed at the upper end of one side of the belt conveyor. The laser scanning is used to obtain the flow of the high-temperature melt in the conveyor chute, generate three-dimensional coordinate data, and apply a filtering algorithm to process the image to remove interference.

[0146] Step S32: Analyze the acquired three-dimensional coordinate data of the laser scan, use point cloud deformation analysis technology to correct the data, and extract the three-dimensional characteristics and volume information of the melt; convert the measured melt volume into the mass flow rate of the material through formula calculation, using the following formula:

[0147]

[0148] where Q 熔体 is the mass flow rate of high temperature melt, ρ 熔体 is the density of the high temperature melt, V熔体 is the measured high-temperature melt volume, t is the measurement time;

[0149] Step S33: Input the monitored material flow data into the intelligent feedback control component to optimize the material delivery plan and grasp the flow changes in real time; according to the monitoring results, adjust the equipment control parameters, optimize the data collection frequency and set the alarm threshold; when the flow is high, increase the frequency of laser scanning.

[0150] Preferably, in step S31 of this embodiment, laser scanning and data acquisition can monitor the flow of high-temperature melt in real time by installing a laser scanning camera on the belt conveyor next to the chute; the three-dimensional coordinate data generated by the laser scanning reflects the actual state of the melt and can provide a data basis for subsequent analysis; a filtering algorithm (average filtering or frequency domain filtering) is applied to process the laser scanning image to remove interference and ensure the clarity and validity of the data. Implementation significance: It provides accurate basic data for the subsequent judgment of coking risk. The accuracy of this link directly affects the validity of subsequent analysis; through filtering, noise interference is eliminated, and the data quality is improved, thereby improving the measurement accuracy of the overall system. Step S32 data analysis and flow calculation uses point cloud deformation analysis technology to correct the acquired three-dimensional coordinate data and accurately extract the three-dimensional characteristics and volume information of the melt; the measured melt volume is converted into the mass flow rate of the material through a formula, and the calculated mass flow rate provides quantitative information on the melt flow. Implementation significance: By calculating the mass flow rate, the flow state of the melt can be quantified, providing a specific numerical basis for subsequent coking judgment; data correction and volume information extraction improve the understanding of the melt flow characteristics, which helps to accurately judge whether there is a coking risk under specific circumstances. Step S33 intelligent feedback and optimization control inputs the monitored material flow data into the intelligent feedback control component to achieve real-time monitoring and analysis of the flow; based on the monitoring results, the intelligent feedback system can automatically adjust the equipment control parameters and optimize the data acquisition frequency, as well as set reasonable alarm thresholds to improve the system response capability; when a high flow rate is detected, the laser scanning frequency is accelerated to achieve a rapid response to changes in the melt flow, facilitating timely measures. Implementation significance: Through data monitoring and feedback control, the material delivery plan can be optimized, thereby improving production efficiency; dynamic adjustment and optimization operations can effectively reduce the probability of coking, improve the fluidity and processing efficiency of materials, and reduce unexpected risks in production.

[0151] In summary, through the three steps above, this embodiment achieves closed-loop management from data collection and analysis to feedback control, enabling real-time monitoring of high-temperature melt flow and effective assessment of coking risks. The technical effects and implementation significance of each step contribute to the ultimate goal, providing strong support for ensuring production safety and efficiency.

[0152] Furthermore, the process of extracting the three-dimensional features and volume information of the melt in step S32 specifically includes the following steps:

[0153] Step S321: Generate a point cloud data set containing the spatial coordinates (X, Y, Z) of the melt; perform geometric correction on the obtained point cloud using deformation analysis to identify the melt part and background, and output the corrected point cloud data, focusing on the actual shape of the melt;

[0154] Step S322: extracting important three-dimensional features based on the corrected point cloud data, including volume, surface area, and shape descriptors (such as aspect ratio, curvature, etc.);

[0155] Step S323: Calculate the volume of the melt by combining the point cloud data with the voxel method, grid reconstruction or integration method; and output the extracted three-dimensional feature data and melt volume information.

[0156] Preferably, step S321 of this embodiment involves point cloud data correction and separation. This involves geometrically correcting the original point cloud data using deformation analysis techniques to correct for geometric distortions caused by errors during the scanning process, thereby making the three-dimensional shape of the melt more accurate. An algorithm is then used to distinguish the melt from the background, ensuring that subsequent analysis focuses solely on the melt's three-dimensional features. The corrected point cloud data specifically expresses the melt's true form, eliminating redundant data and providing a more focused view of the target object. Significance: Accurate geometric correction and background separation help ensure the accuracy of subsequent feature extraction and are the foundation for feature extraction and volume calculation. Appropriate filtering and cleaning of the point cloud data reduces the computational burden of subsequent analysis and improves processing efficiency. Step S322 involves extracting key three-dimensional features of the melt, including volume, surface area, and shape descriptors (such as aspect ratio and curvature). These features can help describe the melt's geometric properties and flow state. By setting shape descriptors (such as moment of inertia and roundness), a more comprehensive analysis of the melt's shape can be performed to identify potential problems in its flow. Implementation significance: The extracted three-dimensional features provide quantitative support for subsequent analysis and judgment, especially playing a key role in determining whether there is a risk of coking; through a comprehensive understanding of the geometric characteristics of the melt, process control and material flow management can be improved to achieve higher production stability and efficiency. Step S323 calculates the melt volume, combined with the extracted point cloud data, to accurately calculate the volume of the melt, which can effectively convert the three-dimensional data into quantitative volume information; completes the output of the melt volume and related three-dimensional feature data for further analysis and decision-making. Implementation significance: Accurate volume calculation provides important parameters for understanding the flow behavior of the melt, helping to formulate corresponding processes and control plans; by analyzing the changing trend of the melt volume, problems in the flow can be identified early, so that preventive measures can be taken before potential failures such as coking occur.

[0157] In summary, the process of extracting 3D melt features and volume information in this embodiment achieves accurate data acquisition, feature extraction, and volume calculation. This not only provides a quantitative basis for in-depth analysis of the melt's physical properties, but also offers important decision-making support for subsequent production process optimization, fault warning, and process improvement.

[0158] Furthermore, the process of identifying the melt portion and the background in step S321 specifically includes the following steps:

[0159] Step S3211: Calculate the average coordinates of each point to generate the global center of a set of data; use the center as a reference point and generate a transformation matrix based on the distances and angles of all points relative to this center; use the transformation matrix to perform a linear transformation on the coordinates of each data point to adjust the positions of all points in the coordinate system;

[0160] Among them, the calculation of the global center is:

[0161] Calculate the average coordinates of all points, that is:

[0162]

[0163] Where N is the total number of points, (x i ,y i ,z i ) are the coordinates of each point.

[0164] Translation transformation:

[0165] Create a translation vector (T = (-Cx, -Cy, -Cz)) to move the center of the point cloud to the origin of the coordinate system to eliminate the overall offset of the point cloud.

[0166] Rotation transformation:

[0167] Set the rotation matrix R and define the rotation around the X, Y or Z axis as needed to adjust the point cloud's posture. The rotation matrix is ​​usually a 3x3 matrix and can be expressed as:

[0168]

[0169] where r ij is the coefficient calculated according to the rotation angle;

[0170] Generate the final transformation matrix: The final total transformation matrix M is usually a 4x4 homogeneous transformation matrix:

[0171]

[0172] Among them (T x ,T y ,Tz ) are the components of the translation part, and the last line is used to represent the homogeneous coordinates;

[0173] In practical applications, for each point P i =(x i ,y i ,z i ,1) T , by multiplying it with the transformation matrix M, we can get the new point coordinates P' i :

[0174] P′ i =M·P i

[0175] The linear transformation of points in the coordinate system is realized, ensuring the accurate representation of the melt geometry;

[0176] Step S3212: Using the spatial distribution of points, calculate the adjacency relationship between points in the point cloud dataset; establish a connection map of adjacent points, and build a local neighborhood model for each point to identify areas with high point density; based on density analysis and a set threshold, remove points in sparse areas to form a pre-screened point cloud dataset;

[0177] Step S3213: Analyze the neighborhood distribution characteristics of each remaining point in the point cloud dataset after removing the initially screened points, quantify the connectivity and spatial characteristics of the neighborhood around each point, and determine whether it meets the structural characteristics of the melt; accurately separate the qualified points from the background points; and obtain a corrected point cloud dataset by screening and filtering the point cloud.

[0178] Preferably, step S3211 of this embodiment calculates the average coordinates of all points to generate a global center, providing a benchmark for geometric correction. Based on the global center, a transformation matrix is ​​created, which defines the mapping relationship from the initial coordinate system to the target coordinate system, allowing all data points to be adjusted in a consistent manner. Each point undergoes a linear coordinate transformation by applying the transformation matrix, thereby eliminating geometric errors generated during the scanning process. Implementation significance: By coordinating the spatial position of the point cloud data, the geometric features of the melt are ensured to be presented in an optimized state, providing an accurate data foundation for subsequent analysis. A unified coordinate standard is established for data collected from different data sources or under different conditions, making processing in subsequent steps more consistent. Step S3212 analyzes the spatial relationship between each point and establishes an adjacency matrix between points, mapping the connections between each point in the dataset. A local model is constructed for each point, from which high-density areas are identified to ensure effective focus on the melt. Based on a preset density threshold, relatively sparse points are eliminated to form a preliminary integrated point cloud dataset. Implementation significance: By eliminating points in low-density areas, the impact of background noise is significantly reduced, ensuring that subsequent data processing is concentrated on the melt part; by identifying and retaining only points with high density, the time and computing resource consumption of subsequent processing are reduced, and the efficiency of the overall process is improved. Step S3213 analyzes the neighborhood distribution characteristics of each point in the point cloud left after the initial screening, and quantifies its spatial characteristics, including connectivity, changes in local density, etc.; based on the geometric characteristics and structure of the melt, it is judged whether these points meet the morphological standards of the melt; through further screening and filtering of the data, the points that meet the shape characteristics of the melt are clearly separated from the background noise, and finally the representative points of the melt are extracted. Implementation significance: By further refining the screening and eliminating unqualified data, it helps to improve the quality and validity of the remaining data, making the data set more representative; after clearly dividing the melt and the background, it can provide high-quality data support for subsequent three-dimensional feature extraction and volume calculation, ensuring the reliability of the analysis results and the effectiveness of business decisions.

[0179] In summary, the extraction of viscous structure and accurate identification of background in this embodiment form a complete processing chain, ensuring data quality at each step, achieving a balance between computational efficiency and result reliability, and providing a strong foundation for further advancement of melt property analysis.

[0180] Furthermore, the process of identifying the area with higher point density in step S3212 specifically includes the following steps:

[0181] Step S32121: Select a neighborhood radius r to determine which neighboring points are included when calculating the local features of each point. The radius is based on a pre-set empirical value. For each point P in the point cloud dataset, i =(xi ,y i ,z i ), and find the points in its neighborhood as follows:

[0182] Traverse all data points P i =(x i ,v i ,z i ), calculate its intersection with point P i The Euclidean distance of:

[0183]

[0184] If d ij , then point P j Include point P i In the neighborhood of

[0185] Step S32122: For each point P i Generate a neighborhood model and use a data structure to store all points in its neighborhood; use a dictionary or hash table to implement it, with the key value pointing to point P i The reference to the value contains a list of neighbors; for each point P i , the neighborhood model now includes its neighboring point set; calculate the point density ρ i :

[0186]

[0187] where N i It's point P i The number of points in the neighborhood, V is the volume of the neighborhood, for a spherical neighborhood:

[0188] Step S32123: By comparing the density value ρ of each point i With the set threshold, those points that meet the conditions are marked, which constitute the preliminary screening results of high-density areas.

[0189] Preferably, step S32121 of this embodiment selects a neighborhood radius r and finds points within the neighborhood. By setting a neighborhood radius, the local range considered for each point in the calculation process is determined, so that the local characteristics of the point can be effectively focused on; by traversing all points and calculating the Euclidean distance, the neighborhood points of each point are identified in real time, thereby forming local structural information in the overall data set. Implementation significance: It lays the foundation for point density calculation, so that the local neighborhood of each point can be clearly defined, and provides the necessary spatial context when analyzing the data distribution of the point cloud; according to the setting of the neighborhood radius, data sets of different densities can be flexibly analyzed, affecting the subsequent recognition effect of high-density areas, making the processing more efficient. Step S32122 generates a neighborhood model and calculates point density, generates a dictionary or hash table for each point to store the set of points in its neighborhood, and facilitates fast access and calculation; by calculating the total number of points and volume in the neighborhood of each point, the point density value is obtained to form a quantized point cloud feature. Implementation significance: Using a dictionary or hash table to store neighborhood points improves the efficiency of space management, facilitates quick search and update of neighborhood information for each point, and facilitates subsequent analysis; provides a quantitative assessment of point cloud density, which helps to understand the distribution characteristics of points in the data set. The result of the density calculation is the basis for subsequent high-density area screening. Step S32123 marks the high-density area, and by comparing the density of each point with the set threshold, quickly marks the points that meet the conditions to form a preliminary screening result for the high-density area; the points in the high-density area are clearly defined and can be distinguished from the data in other low-density areas, providing a clear target point set for subsequent data processing. Implementation significance: By retaining only high-density points, the computational complexity of subsequent analysis is significantly reduced, and the processing efficiency of subsequent steps is improved; the identified high-density areas are related to the characteristics of the melt, which facilitates subsequent structural analysis, such as object recognition, feature extraction and morphological analysis, which directly affects the accuracy and effectiveness of the final analysis results.

[0190] In summary, each step in this embodiment plays a critical role in the identification of high-density areas. From data processing and storage to analysis and result extraction, a complete analytical chain is formed. This ensures that the identified high-density areas reflect the true characteristics of the point cloud data, providing a foundation for subsequent operations in practical applications. Overall, the implementation of these steps improves the validity and accuracy of point cloud data, supporting more complex subsequent analytical tasks.

[0191] Furthermore, the process of determining whether the structure characteristics of the melt are met in step S3213 specifically includes the following steps:

[0192] Step S32131: For each point's neighborhood, calculate the shape features and calculate the normal vector through principal component analysis of the neighborhood points. The normal vector understands the geometric features of the melt and characterizes the curvature of the surface around the point. The melt usually exhibits curvature characteristics.

[0193] Step S32132: Construct a connection graph based on the neighbor relationship, use graph theory methods to analyze the connectivity between points; use the connected component labeling method to find areas with high density and structural connectivity;

[0194] Step S32133: By comparing the normal vector direction distribution, point density distribution and shape characteristics of the point cloud with the predetermined melt characteristics, the matching index is calculated, and the distance and similarity between the point cloud and the model are calculated; the melt part is judged according to the set threshold, the points that meet the melt structure characteristics are marked, and the points that do not meet the characteristics are excluded to form the final screened point cloud data set.

[0195] Preferably, step S32131 of this embodiment calculates shape features. By using the principal component analysis (PCA) method, the normal vector (i.e., the direction of the surface tangent) is calculated based on the distribution of neighborhood points, providing a quantitative description of the geometric shape of the point cloud; by calculating the curvature of the neighborhood points, the curvature of the surface around the point is further analyzed. The curvature value can indicate the smoothness of the melt surface and the local shape change. Implementation significance: Geometric features can be extracted from point cloud data, making the shape features of the melt clearer; shape features are the key to understanding the structure of an object and lay the foundation for feature matching; judging the smoothness and continuity of the point cloud area based on shape features and curvature helps to distinguish the melt part from background or noise data, thereby improving the accuracy of data processing. Step S32132 constructs a connection map and connectivity analysis. Based on the adjacency relationship between points, a graph structure is constructed to indicate which points in the point cloud are connected or adjacent to each other; through graph theory methods, the connected components in the point cloud are marked, which can effectively identify dense, structurally coherent areas. Implementation significance: Through connectivity analysis, melt parts with overall regional characteristics can be discovered and marked, rather than isolated scattered points; continuity is an important manifestation of melt characteristics, because it helps to determine the integrity of the melt part; by focusing on analyzing high-density and connected areas, the amount of calculation for subsequent feature analysis can be reduced, and the data processing process can be optimized. Step S32133 Feature matching and threshold judgment compares the normal vector direction, density distribution, and shape characteristics of the point cloud, calculates the similarity index with the known melt feature model, and uses mathematical models (such as Euclidean distance, cosine similarity, etc.) for matching; judges according to the preset threshold standard, and marks the points that meet the conditions as melt, otherwise they are marked as background. Implementation significance: By systematically comparing the features of the point cloud, it is helpful to achieve accurate distinction between the melt part and the background; accurate classification results are extremely important for subsequent applications (such as shape analysis, model reconstruction, etc.); using threshold judgment and model matching, a quantitative and repeatable evaluation method is provided, making the data processing process more standardized, which can effectively adapt to different scenarios and requirements in practical applications.

[0196] In summary, this embodiment plays a key role in determining melt structural characteristics, ensuring the effectiveness and accuracy of feature extraction, structural analysis, and feature matching. These steps enable effective processing of cluttered point cloud data, extracting meaningful elements and providing a reliable data foundation for subsequent analysis, modeling, and applications. This also further enhances the importance of point cloud technology in practical applications such as 3D reconstruction, automated inspection, and manufacturing process analysis.

[0197] This embodiment also provides an embodiment of an automated chute heat preservation and anti-coking device. In this embodiment, the automated chute heat preservation and anti-coking device is applied to the automated chute heat preservation and anti-coking system in the above embodiment. The automated chute heat preservation and anti-coking device specifically includes: a high-temperature wireless temperature sensor 6, a heating element 7, a laser scanning camera 8, and a coke cleaning device 9;

[0198] Among them, the high-temperature wireless temperature sensor 6, the heating element 7, the laser scanning camera 8 and the de-coking device 9 are connected to the intelligent feedback component 5;

[0199] Preferably, the high-temperature wireless temperature sensor 6 of this embodiment can accurately measure the temperature in the chute in a high-temperature environment and transmit the data to the control system wirelessly, with anti-interference ability and high stability; it monitors the temperature changes in the chute in real time to ensure that the temperature is maintained within the set range to prevent the temperature from being too low and causing the material to coke. Under the feedback control of the temperature sensor 6, the heating element 7 (such as an electric heating pipe, hot air furnace, etc.) is responsible for maintaining or raising the temperature of the material by heating the chute; the heating element 7 can automatically adjust according to actual needs to ensure uniform heating; maintain the temperature in the chute stable to prevent coking due to insufficient temperature during the flow of materials. The laser scanning camera 8 can obtain the material morphology and distribution information in the chute in real time, and obtain high-precision three-dimensional images by projecting laser beams. The three-dimensional images help track the flow state and height changes of the material; provide real-time feedback and monitoring to ensure smooth flow of materials in the chute, and promptly detect and deal with coking or blockage problems. After detecting coking, the coke cleaning equipment 9 can clean the coked material through mechanical or physical means (such as vibration, scraping or impact). Combined with the feedback from the laser scanning camera 8, it can accurately identify the location and degree of coking; clean the coke in real time to ensure smooth material flow and reduce production stagnation and maintenance work.

[0200] In summary, this embodiment can realize real-time monitoring of the temperature and material status in the chute, ensuring that thermal management and material flow are in the optimal state; the cooperation of the integrated high-temperature wireless temperature sensor 6 and the heating element 7 can effectively prevent the material from coking during the transmission process and improve the system reliability; the cooperation of the laser scanning camera 8 and the decoking equipment 9 can quickly detect and deal with the coking problem, thereby reducing the time of sudden failures and maintenance.

[0201] This embodiment prevents material coking and reduces downtime caused by equipment failure, thereby improving production continuity and efficiency. Real-time temperature monitoring and intelligent heating make the heating process more efficient, reduce ineffective energy consumption, and thus reduce production costs. Maintaining the material at an optimal temperature helps improve the quality of the final product and avoid product defects caused by coking. It can also reduce unnecessary maintenance and overhauls, improve the reliability and long-term effectiveness of the equipment, and thus enhance the competitiveness of the enterprise. This has formed a highly efficient and intelligent automated chute insulation and anti-coking device, greatly improving temperature control accuracy and material flowability, and its significance for industrial production is far-reaching.

[0202] Furthermore, if Figure 8 As shown, the high-temperature wireless temperature sensor 6 is embedded in the refractory layer 10, the inner side of the refractory layer 10 is a chute 11, and the interior of the chute 11 is a high-temperature melt 12;

[0203] At a specific position of the chute 11, n (range 3 to 5) high-temperature wireless temperature sensors 6 are arranged in the circumferential direction, which is regarded as one layer; in the conveying direction of the chute 11, one layer is arranged every h (range 20 to 50 cm), from the bottom of the kiln along the chute 11 to the next kiln, for a total of m layers;

[0204] like Figure 9 As shown, the heating elements 7 are embedded in the refractory layer 10 and arranged at intervals of h (range 20-50 cm) in the conveying direction of the chute 11. The high-temperature wireless temperature sensors 6 are interspersed and arranged from the bottom of the kiln along the chute 11 to the next kiln, with a total of m layers.

[0205] like Figure 10 As shown, a belt conveyor 14 is established in parallel with the chute 11, and a laser scanning camera 8 is placed on the upper end of one side thereof to obtain the flow of the high-temperature melt 12 in the conveying chute 11 through laser scanning;

[0206] like Figure 11 As shown, a coke-clearing device 9 is positioned above the chute 11, lower than the laser scanning camera 8. This device comprises a travel track 16, a transverse moving tube 17, a coke-clearing arm 15, and a coke-clearing device. The coke-clearing arm 15 is retractable to ensure it can be moved to any position within the chute 11. Driven by the intelligent feedback component 5, it begins operation when the laser scanning camera 8 detects coke buildup and provides detailed location information.

[0207] The intelligent feedback component 5 operates the coke cleaning device 9 to move on the travel track 16, and adjusts the position on the horizontal moving tube 17, and aligns the telescopic coke cleaning arm 15 with the coke-forming part, and finally uses the coke cleaning device 9 to automatically remove the coke from the chute 11. The coke cleaning device 9 includes a riser tube wall waste heat recovery heat exchanger, an internal plug-in heat exchanger and a coke cleaning drive screw driven coke cleaning device 9. The internal plug-in heat exchanger, the coke cleaning drive screw and the online coke cleaning drive device are assembled into a modular plug-in device. The outer sleeve type lead screw tube is provided with an "8" shaped thread. The coke cleaning drive device drives the driving worm and the driven drive turbine transmission to realize the rotation of the lead screw tube, so that the rotating lead screw tube drives the lead screw slider on its lead screw to move up and down. The lead screw slider is fixedly connected to the coke cleaning device 9, driving the coke cleaning device 9 to move up and down. The coke cleaning device 9 is matched with the inner diameter clearance of the riser, driving the coke cleaning device 9 to move up and down in the riser, thereby realizing coke cleaning; the lower part of the coke cleaning drive screw is respectively provided with The first coke cleaning hammer and the second coke cleaning hammer are softly connected to the first chain and the second chain. The coke cleaning method is that the coke cleaning driving screw rotates to drive the first coke cleaning hammer and the second coke cleaning hammer at the far ends of the first chain and the second chain to rotate, and the rotation generates centrifugal force so that the first coke cleaning hammer and the second coke cleaning hammer with coke generate friction and collision relative motion with the riser pipe seat and the coke oven mouth respectively, to achieve coke cleaning action, the angular velocity of the rod rotation driven by the rotation of the coke cleaning driving screw to drive the first coke cleaning hammer and the second coke cleaning hammer to rotate is ω, the rotation of the coke cleaning driving screw drives the first coke cleaning hammer and the second coke cleaning hammer to rotate until the angular velocity ω=0, so that the first coke cleaning hammer and the second coke cleaning hammer and the links between the first chain and the second chain sag to generate mutual friction and collision to achieve coke cleaning.

[0208] like Figure 12 As shown, this embodiment provides an embodiment of an electronic device. In this embodiment, the electronic device 18 includes a processor 181 and a memory 182 coupled to the processor 181.

[0209] The memory 182 stores program instructions for implementing the automated chute heat preservation and anti-coking method of any of the above embodiments.

[0210] The processor 181 is used to execute the program instructions stored in the memory 182 to perform automatic chute heat preservation and anti-coking.

[0211] The processor 81 may also be referred to as a CPU (Central Processing Unit). The processor 181 may be an integrated circuit chip having signal processing capabilities. The processor 181 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The general-purpose processor may be a microprocessor or any conventional processor.

[0212] Further, Figure 13 This is a schematic diagram of the structure of the storage medium of an embodiment of the present application. The storage medium 19 of the embodiment of the present application stores program instructions 191 that can implement all the above methods, wherein the program instructions 19 can be stored in the above storage medium in the form of a software product, including a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0213] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0214] In addition, the functional units in the various embodiments of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units. The above is only an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

[0215] The above detailed description of the specific embodiments of the invention is intended to be illustrative only, and the present invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications or substitutions to the invention are also within the scope of the present invention. Therefore, equivalent changes, modifications, and improvements made without departing from the spirit and scope of the present invention are also encompassed within the scope of the present invention.

Claims

1. An automated chute heat preservation and anti-coking system, characterized in that: The automated chute heat preservation and anti-coking system includes: A temperature monitoring component is used to arrange multiple temperature acquisition devices in the groove of the refractory material layer on the back of the chute. The temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output; The heating and insulation component is used to start heating elements in two adjacent parts of a certain area under the control of the intelligent feedback component when the temperature value of a certain area of ​​the chute is lower than the critical value; The coking visual monitoring component is used to obtain the flow rate of the high-temperature melt in the chute, determine whether coking occurs in an area within the chute, and send the coordinates of the coking area to the intelligent feedback component; The automatic coke removal component is used to clear the coked area through the coke clearing equipment under the control of the intelligent feedback component; The intelligent feedback component is used to control the temperature monitoring component, the heating and heat preservation component, the coke visual monitoring component, and the coke automatic removal component. It receives feedback data from the temperature monitoring component, the heating and heat preservation component, the coke visual monitoring component, and the coke automatic removal component. When coke is detected in the chute, the heating and heat preservation component maintains the heating state, and the coke automatic removal component starts to perform coke removal based on the position provided by the coke visual monitoring component. Heating and insulation components, including: The element layout module is used to set up multiple areas inside the chute, each area is equipped with a heating element to achieve local heating; Zone heating module, which is used to install heating elements in the refractory layer outside the chute wall to form a circular heating zone; multiple heating zones are arranged outside the chute to form a preliminary heating grid; The numerical comparison module is used to monitor the output of the temperature acquisition device in real time. When the temperature of a certain area is lower than the set critical value, it responds by automatically adjusting the adjacent heating elements to turn on and stop heating when the final temperature is higher than the critical value. Coking visual monitoring components, including: A data processing module is used to obtain three-dimensional point cloud data and three-dimensional coordinate data of the flow image of the high-temperature melt in the chute through a scanning device. The three-dimensional point cloud data is used to capture the dynamic shape and flow characteristics of the melt. The flow image is preprocessed, including filtering, to obtain preprocessed three-dimensional point cloud data; The flow change module is used to correct the 3D point cloud data through point cloud deformation analysis, extract the 3D characteristics and volume information of the melt, calculate the material mass flow rate per unit time, and monitor the changes in mass flow rate; The coking judgment module is used to determine that coking may occur in the current area when the monitored flow rate has obvious fluctuations and reaches the set threshold, and transmit the location information to the intelligent feedback component for processing.

2. The automated chute heat preservation and anti-coking system according to claim 1, characterized in that: Temperature monitoring components, including: The signal acquisition module is used for temperature acquisition equipment to directly contact the chute wall through the adjacent thermocouple or thermal resistance sensor to obtain actual temperature information; the detected temperature information is converted into an analog voltage signal proportional to the temperature; the analog voltage signal is amplified, filtered and linearized to obtain a conditioned analog voltage signal; The analog-to-digital conversion module is used to input the conditioned analog signal into the analog-to-digital converter and quantize the analog voltage value of each sample into a corresponding digital value; the converted digital signal is smoothed by the digital signal processor; The signal output module is used to output the temperature value after digital signal processing through the interface for processing and judgment by the intelligent feedback component.

3. The automated chute heat preservation and anti-coking system according to claim 1, characterized in that: Automatic coke removal components, including: The travel and positioning module is used to control the movement of the decoking equipment, including the movement of the travel track and the position adjustment of the transverse moving tube; it is used to perform positioning when the laser scanning camera detects coking; The coke clearing arm and drive module is used to extend and retract the coke clearing arm and move the coke clearing equipment to the coke deposited area in the chute to complete the coke clearing operation. It contains multiple drive mechanisms that automatically align with the coke deposited area and perform coke clearing upon receiving signals from the intelligent feedback system. The coke clearing operation module is used to utilize the provided coke clearing equipment to thaw, rub and collide the coked materials, and to make them fall off from the chute wall through the centrifugal force generated by the rotating coke clearing hammer.

4. The automated chute heat preservation and anti-coking system according to claim 1, characterized in that: Smart feedback components, including: A data receiving and processing module is used to receive feedback data from the temperature monitoring component, the coking visual monitoring component and the coking automatic removal component, including temperature values, flow information and coking locations; The control and regulation module is used to control the heating elements of the heating and insulation components based on the monitored temperature and coking status. The intelligent feedback component starts heating when needed to maintain the temperature of the chute within an appropriate range. It also starts the relevant operations of the automatic coking removal component. When the coking visual monitoring component detects the occurrence of coking, it directs the coking cleaning equipment to automatically remove coking. The decision-making function module is used to perform intelligent analysis, make corresponding decisions, and adjust the defocusing frequency under different operating conditions.

5. An automated chute heat preservation and anti-coking method, which is applied to the automated chute heat preservation and anti-coking system according to any one of claims 1 to 4, characterized in that: The automated chute heat preservation and coking prevention method comprises: Multiple temperature acquisition devices are arranged in the grooves of the refractory material layer on the back of the chute. The temperature acquisition devices are used to measure the temperature of the chute wall area, obtain analog signals, and convert the analog signals into digital signals for output; When the temperature value of a certain area of ​​the chute is lower than the critical value, the heating elements of two adjacent parts of the area are activated to heat; Obtain the flow rate of the high-temperature melt in the chute, determine whether coking occurs in an area within the chute, and obtain the coordinates of the area where coking occurs; and use the coking equipment to decoke the coked area.

6. The automatic chute heat preservation and anti-coking method according to claim 5, characterized in that: The heating elements of two adjacent parts of a certain area are activated, including: Temperature acquisition devices are installed at multiple locations within the chute to monitor the temperature of different areas in real time. The temperature acquisition devices continuously acquire temperature data of the melt material within the chute and feed it back to the intelligent feedback system. The intelligent feedback component sets a critical value t based on the characteristics of the melt material to determine whether there is a coking risk. When the temperature displayed by the temperature acquisition device in a certain area is lower than the critical value t, the current area is determined to have a potential coking risk. The intelligent feedback component controls two adjacent heating elements to start heating. The heating elements are installed in the refractory material outside the chute wall and provide heat to the heating area through a circular path. After the heating elements are working, the temperature gradually rises until the temperature detected by the temperature acquisition device is 10° higher than the critical value t, that is, when it reaches t + 10°, the heating will stop. In the conveying direction of the chute, a layer of heating elements is arranged every h times, staggered with the temperature collection equipment; from the bottom of the kiln to the next kiln, m layers of heating elements are arranged along the chute to ensure uniform temperature and form multi-layer heating from bottom to top; during the heating process, the temperature collection equipment continuously obtains data, and the intelligent feedback component detects the temperature changes in each area in real time; if the monitored temperature drops below the critical value t again, the heating process of the two adjacent parts of the heating elements is repeated.

7. The automatic chute heat preservation and anti-coking method according to claim 5, characterized in that: Determine whether coking occurs in the area within the chute, including: A belt conveyor is built parallel to the chute, and a laser scanning camera is placed on the upper end of one side. Laser scanning is used to obtain the flow of high-temperature melt in the conveyor chute, generate three-dimensional coordinate data, and apply a filtering algorithm to process the image to remove interference. The acquired 3D coordinate data from laser scanning is analyzed, and point cloud deformation analysis technology is used to correct the data to extract the 3D characteristics and volume information of the melt. The measured melt volume is converted into the mass flow rate of the material through formula calculation. The monitored material flow data is input into the intelligent feedback control component to optimize the material delivery plan and grasp the flow changes in real time; based on the monitoring results, the equipment control parameters are adjusted, the data collection frequency is optimized, and the alarm threshold is set; when high flow is detected, the frequency of laser scanning is increased.

8. An automatic chute heat preservation and anti-coking device, which is applied to the automatic chute heat preservation and anti-coking method according to claim 5, characterized in that: The automated chute heat preservation and anti-coking device includes: a high-temperature wireless temperature sensor, a heating element, a laser scanning camera and a coke cleaning device; Among them, high-temperature wireless temperature sensors, heating elements, laser scanning cameras and defocusing equipment are connected to the intelligent feedback component; The high-temperature wireless temperature sensor is embedded in the refractory layer. The inner side of the refractory layer is a chute, and the inside of the chute is a high-temperature melt. The heating element is embedded in the refractory layer and arranged in the conveying direction of the chute, with the high-temperature wireless temperature sensor interposed between them; A belt conveyor is built parallel to the chute, and a laser scanning camera is placed on the upper end of one side of the belt conveyor to obtain the flow conditions of the high-temperature melt in the conveying chute through laser scanning; A decoking device is placed above the chute, at a lower height than the laser scanning camera. A travel track, a transverse moving tube, and a decoking arm are also installed above the chute. The decoking arm can be freely extended and retracted to ensure that it can be moved to various positions in the chute. Driven by an intelligent feedback component, it starts working when the laser scanning camera detects coking and provides its specific location information.

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