A method and system for predicting online sintering return rate based on thermal imaging of tail section

Abstract

The present invention discloses an online sintering return rate prediction method and system based on tail section thermal imaging, comprising the following steps: obtaining the actual effective tail section thermal imaging of the current batch of trolleys; obtaining the current sintering section full cross-sectional interval and the current sintering critical temperature interval of the trolley sintering material of the current batch of trolleys based on the actual effective tail section thermal imaging; obtaining the current raw material area ratio of the current sintering raw material interval based on the ratio of the current sintering critical temperature interval and the current sintering section full cross-sectional interval; inputting the current raw material area ratio and the current sintering operating condition parameters into the return rate prediction model to predict the current sintering return rate of the current batch of trolleys. The online sintering return rate prediction method based on tail section thermal imaging provided by the present invention obtains the sintering return rate in real time, avoiding the existing need to obtain the sintering return rate through screening and weighing, resulting in the inability to adjust the sintering operating conditions according to the sintering return rate in a timely manner, and the technical problem of low sintering efficiency.

Description

Technical Field

[0001] The present invention relates to the field of sintering technology, and in particular to an online sintering return rate prediction method and system based on machine tail section thermal imaging. Background Art

[0002] With the rapid development of modern industry, the scale of steel production is growing, and energy consumption is also increasing. Energy conservation and environmental protection indicators are becoming increasingly important considerations in the steel production process. In steel production, iron-containing raw ore needs to be processed through a sintering system before entering the blast furnace for smelting. This is to process various powdered iron-containing raw materials, add appropriate amounts of fuel (coal powder, coke powder) and flux, add an appropriate amount of water, mix and pelletize, and then place them on a sintering trolley for roasting. This process causes a series of physical and chemical changes to occur, forming a sintered ore that is easy to smelt. This process is called sintering.

[0003] The sintering process includes ignition and sintering, crushing, cooling with a ring cooler, and screening. The oversize material after screening is the finished sintered ore, while the undersize material after screening is sintered back into the ore. In existing technology, the sintering back into the ore rate is calculated by weighing the oversize and undersize materials. However, due to the long cooling time of the sintering machine during the ring cooler, the sintering back into the ore rate cannot be predicted immediately after the sintering machine completes sintering. This results in a significant lag in the sintering back into the ore rate, making it difficult to adjust the sintering conditions in a timely manner based on the sintering back into the ore rate, resulting in low sintering efficiency.

[0004] In view of this, it is necessary to propose an online sintering return rate prediction method and system based on tail section thermal imaging to alleviate the above defects. Summary of the Invention

[0005] The present invention provides an online sintering return rate prediction method and system based on machine tail section thermal imaging, which solves the existing technical problems of failure to obtain the sintering return rate in a timely manner and low sintering efficiency.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A method for predicting the online sintering return rate based on thermal imaging of the tail section of a machine comprises the following steps:

[0008] S10, obtain the actual effective tail sintering cross-section thermal image of the current batch of trolleys, and the actual effective tail sintering cross-section thermal image has a known correlation ratio with the real cross-section image of the current batch of trolleys; S20, obtain the current sintering cross-section full-section interval and the current sintering critical temperature interval of the trolley sintering material of the current batch of trolleys according to the actual effective tail sintering cross-section thermal image, the temperature range value of the current sintering critical temperature interval is 600℃ to 1280℃, and the current sintering critical temperature interval is located within the current sintering cross-section full-section interval; S30, calculate the current raw material area share of the current sintering raw material interval according to the ratio of the current sintering critical temperature interval and the current sintering cross-section full-section interval; S40, input the current raw material area share and the current sintering operating parameters into the return ore prediction model to predict the current sintering return ore rate of the current batch of trolleys, wherein the historical sintering raw material area share and the historical sintering operating parameters are used as the training input set, and the historical tail raw material return rate is used as the training output set to establish a return ore prediction model through neural network learning.

[0009] Furthermore, the area of ​​the current sintering critical temperature interval in the entire cross-sectional interval of the current sintering section and the area above the current sintering critical temperature interval are determined as the current sintering clinker interval; the current clinker area proportion of the current sintering clinker interval is obtained according to the ratio of the current sintering clinker interval and the current sintering critical temperature interval, and the current raw material area proportion is determined according to the current clinker area proportion, and the sum of the current raw material area proportion and the current clinker area proportion is 1.

[0010] Furthermore, it also includes the steps of: obtaining the bottom material interval of the current batch of trolleys based on the actual effective tail sintering section thermal imaging, the bottom material interval being the space occupied by the actual bottom material on the bottom surface of the current batch of trolleys; determining the area between the current sintering critical temperature interval and the bottom material interval in the current sintering section full section interval as the current sintering raw material section interval; obtaining the current raw material area ratio based on the ratio of the current sintering raw material section interval to the current sintering section full section interval.

[0011] Furthermore, the ideal sintering thermal image of the current batch of trolleys is obtained, and the ideal sintering thermal image includes a theoretical paving layer; the ideal sintering thermal image and the actual effective tail sintering cross-section thermal image are integrated, and the bottom material paving interval is determined according to the theoretical paving layer.

[0012] Furthermore, the method further includes the steps of obtaining the highest temperature interval of the actual effective tail sintering section thermal imaging, and if the temperature range value of the highest temperature interval is not less than the preset temperature range value, determining the highest temperature interval as the current sintering critical temperature interval.

[0013] Furthermore, the historical sintering operating condition parameters include historical sintering air volume parameters, historical trolley speed parameters, and historical sintering material layer thickness parameters.

[0014] Furthermore, step S10 specifically includes: obtaining the initial actual sintering cross-sectional thermal imaging image of each target sintering trolley corresponding to the current batch of trolleys; filtering out the distorted initial actual sintering cross-sectional thermal imaging image; performing image processing on the initial actual sintering cross-sectional thermal imaging image after filtering out the distortion; overlapping and averaging the initial actual sintering cross-sectional thermal imaging image after image processing to obtain the actual effective tail sintering cross-sectional thermal imaging of the current batch of trolleys.

[0015] The present invention also provides an online sintering return rate prediction system based on thermal imaging of the tail section of the sintering machine, which includes a sintering machine, a sintering trolley, a thermal imaging acquisition device and a processing device. The sintering trolley is movably arranged along the sintering machine head wheel toward the sintering machine tail wheel. The sintering machine is provided with a distribution area, an ignition furnace area and an insulation furnace area in sequence at one end close to the sintering machine head wheel; the thermal imaging acquisition device is arranged on the outside of the sintering machine tail wheel of the sintering machine, and the thermal imaging acquisition device is used to obtain the actual effective tail sintering cross-section thermal image of the current batch of trolleys; the processing device is used to execute the steps of the above-mentioned online sintering return rate prediction method based on thermal imaging of the tail section of the sintering machine.

[0016] The present invention has the following beneficial effects:

[0017] The present invention provides an online sintering return rate prediction method and system based on tail section thermal imaging. Based on the research on sintering technology, the actual effective tail section thermal imaging of the sintering machine is timely obtained from the tail wheel position of the sintering machine. The actual effective tail section thermal imaging of the sintering machine has a known correlation ratio with the real cross-sectional image of the current batch of trolleys. The current sintering section interval and the current sintering critical temperature interval are obtained by thermal imaging technology, and the current raw material area ratio is obtained from the tail wheel position of the sintering machine. Finally, the sintering return rate is obtained based on the return prediction model, the current raw material area ratio and the current sintering working condition parameters. The sintering return rate can be predicted when the sintering machine passes the tail wheel of the sintering machine. The online sintering return rate prediction method based on tail section thermal imaging provided by the present invention obtains the sintering return rate in real time, avoiding the existing need to obtain the sintering return rate after screening and weighing, resulting in the inability to adjust the sintering working condition according to the sintering return rate in time, and the technical problem of low sintering efficiency.

[0018] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0020] Figure 1This is the process flow chart of the existing sintering system;

[0021] Figure 2 This is a schematic diagram of the existing sinter formation, where: Figure 2 a is the existing sinter formation process diagram, Figure 2 b is the existing sinter formation cross-section diagram, Figure 2 c is the completed cross-section of the existing sintered ore;

[0022] Figure 3 This is a flow chart of the online sintering return rate prediction method based on machine tail section thermal imaging of the present invention;

[0023] Figure 4 A schematic diagram of thermal imaging of an actual effective tail sintering section in one embodiment of the present invention;

[0024] Figure 5 A partial structural diagram of the online sintering return rate prediction system based on machine tail section thermal imaging of the present invention. DETAILED DESCRIPTION

[0025] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0026] 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.

[0027] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0028] In addition, the descriptions of "first", "second", etc. in the present invention are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0029] The sintering system mainly includes sintering trolley, mixer, main exhaust fan, ring cooler and other equipment. Figure 1 As shown, various raw materials are proportioned in the batching chamber to form a mixture. The mixture enters the mixer for mixing and pelletizing, and then is evenly distributed on the sintering trolley by a circular roller feeder and a nine-roller distributor to form a sintering mixture layer. The ignition fan and the ignition pilot fan start the ignition furnace, which ignites the sintering mixture on the top layer of the sintering trolley. The ignited combustion zone begins to move from top to bottom, and the mixture passing through the combustion zone is roasted into sintered ore. This is the sintering process. The sintered ore obtained after sintering is crushed by a single roller crusher and cooled in an annular cooler. Finally, it is screened and sized before being sent to the blast furnace or finished ore bin. The oxygen required for the sintering process is provided by the main exhaust fan. Multiple vertically arranged bellows are installed below the sintering trolley. Below the bellows is a horizontally mounted large flue (or flue). The large flue is connected to the main exhaust fan. The negative pressure air generated by the main exhaust fan through the flue and bellows passes through the trolley, providing combustion air for the sintering process. Among them, the screened undersize includes raw meal undersize and clinker undersize. The raw meal undersize and clinker undersize are transported on the return ore belt. The materials are all small black-brown particles or powdery materials. The existing technology makes it difficult to timely distinguish the proportion of clinker return ore and raw meal return ore at the tail of the sintering machine.

[0030] Please refer to Figure 2 ( Figure 2 a. Figure 2 b and Figure 2 c) During the sintering process, the ignited combustion zone moves from top to bottom, and the moving speed of the combustion zone is the vertical sintering speed; the sintering trolley moves from the head to the tail (sintering machine tail wheel), and the moving speed of the sintering trolley is the sintering machine speed; when the combustion zone moves to the bottom of the sintering trolley mixture, the corresponding position of the sintering trolley relative to the sintering machine head (or sintering machine tail wheel) is the sintering end point. Figure 2 As shown in a, with the movement of the sintering trolley, the combustion zone gradually moves downward, and the mixture passing through the combustion zone is roasted into sintered ore; Figure 2 As shown in b, during the sintering process, the materials in the sintering trolley can be divided into the bottom material layer, the mixed material layer, the combustion zone layer, and the sintered ore layer from bottom to top. Figure 2 As shown in c, when the combustion zone moves to the bed material layer, the materials in the sintering trolley have all been roasted into sintered ore. At this time, the corresponding position is the sintering end position, which is generally represented by the bellows number. Optionally, the combustion zone layer has a certain thickness, and the sintering end position can be understood as the bottom of the combustion zone just touching the bed material layer. When the sintering end position is controlled at the second to last bellows or the first to last bellows, no raw meal will be produced, the fuel utilization rate will be high, and the sintering efficiency will be high. Optionally, if the bottom of the combustion zone does not touch the bed material layer when the first to last bellows is reached, raw meal will be produced between the bottom of the combustion zone and the bed material layer.

[0031] Please refer to Figure 1 and Figure 2 Through research on sintering technology, it was found that the sintering ore formation process is the process of the sintering combustion zone gradually moving downward. The combustion temperature of the sintering combustion zone is 1250℃ (sintering material temperature). The sintering mixture is mixed with various components such as fuel, flux, iron ore, etc. After the sintering material surface is ignited at the ignition furnace at the head of the sintering machine, a combustion zone with a thickness of about 20 to 30mm is formed. The various mixtures in the combustion zone are roasted at high temperature to form sintered ore. After the combustion zone gradually moves downward to the bottom of the sintering trolley to lay the bottom material layer, the combustion zone will no longer move downward. The fuel in the area through which the combustion zone passes has been completely burned. Among them, during the process of the combustion zone gradually moving downward, the sintering machine trolley also moves towards the sintering machine tail wheel, and the sintering machine trolley moves to the tail of the sintering machine.

[0032] Through the study of sintering technology, during the sintering process, the sintering mixture is spread on the sintering trolley and roasted into sintered ore on the sintering trolley. As the sintering machine trolley moves to the tail of the machine, the sintered ore on the sintering trolley will slide from the tail of the sintering machine to the single roller crusher in units of trolleys. The crushed sintered ore enters the ring cooler (or cooling equipment such as belt cooler) for cooling. The cooled sintered ore enters the screening link, and the powdered material under the screen will be sent back to the batching link and re-enter the sintering machine. This part of the material under the screen and sent back to the batching link is the return ore; the more return ore, the more unfavorable it is for sintering production. For example, if the sintering machine outlet material is 100% and the return ore is 20%, then the sintered product is only 80% of the sintering outlet material. If the return ore is 5%, the product has a sintering outlet material. 95%, the lower the return rate, the higher the utilization rate of the sintering machine; there are raw return and clinker return in the sintering return. Raw return means that part of the mixture on the sintering trolley has not entered the sintering process, and the mixture has not been roasted into sintered ore. It will become powder during the sintering cooling process. Most of these powder materials will be screened out in the screening process (for example, particle size <3mm), which is raw return; clinker return means that some sintered ores are broken into powder due to friction, falling in the feeding process and other factors in the process from the sintering machine to the screening process, and will also be screened out in the screening process; the main reason for the formation of raw return is that some mixture has not completed the sintering process, and the main reason for the formation of clinker return is that the strength of the sintered ore is not enough. To control raw return and clinker return, different means are used in sintering production.

[0033] Please refer to Figure 3 、 Figure 4 and Figure 5The present invention provides an online sintering return rate prediction method based on tail section thermal imaging, comprising the following steps: S10, obtaining the actual effective tail section thermal imaging of the current batch of trolleys, the actual effective tail section thermal imaging of the current batch of trolleys having a known correlation ratio with the real section image of the current batch of trolleys; S20, obtaining the current sintering section full section interval and the current sintering critical temperature interval of the trolley sintering material of the current batch of trolleys according to the actual effective tail section thermal imaging of the current batch of trolleys, the temperature range of the current sintering critical temperature interval is 600°C to 1280°C, and the current sintering critical temperature interval is 1280°C. The critical temperature interval is located within the entire cross-sectional interval of the current sintering section; S30, the current raw material area ratio of the current sintering raw material interval is calculated based on the ratio of the current sintering critical temperature interval and the entire cross-sectional interval of the current sintering section; S40, the current raw material area ratio and the current sintering operating condition parameters are input into the return ore prediction model to predict the current sintering return ore rate of the current batch of trolleys, wherein the historical sintering raw material area ratio and the historical sintering operating condition parameters are used as the training input set, and the historical machine tail raw material return rate is used as the training output set to establish a return ore prediction model through neural network learning.

[0034] The online sintering return rate prediction method based on tail section thermal imaging provided by the present invention is based on the research on sintering technology. By timely obtaining the actual effective tail section thermal imaging of the sintering machine from the tail wheel position of the sintering machine, the actual effective tail section thermal imaging of the sintering machine has a known correlation ratio with the real cross-sectional image of the current batch of trolleys. The current sintering section interval and the current sintering critical temperature interval are obtained by thermal imaging technology, and the current raw material area ratio is obtained from the tail wheel position of the sintering machine. Finally, the sintering return rate is obtained based on the return prediction model, the current raw material area ratio and the current sintering working condition parameters. The sintering return rate can be predicted when the sintering machine passes the tail wheel of the sintering machine. The online sintering return rate prediction method based on tail section thermal imaging provided by the present invention obtains the sintering return rate in real time, avoiding the existing need to obtain the sintering return rate after screening and weighing, resulting in the inability to adjust the sintering working condition according to the sintering return rate in time, and the technical problem of low sintering efficiency.

[0035] It is understandable that thermal imaging technology is a prior art. Through thermal imaging technology, it is possible to obtain the thermal imaging temperature partition intervals of the actual effective tail sintering cross-section thermal imaging. Optionally, the temperature range of the current sintering critical temperature interval is 600°C to 1280°C, and the current sintering critical temperature interval is the highest temperature interval within the accuracy range of the thermal imaging. For example, the thermal imaging accuracy is divided into a level every 50°C. The actual effective tail sintering cross-section thermal imaging includes the 800-850°C interval, the 850-900°C interval, the 900-950°C interval, the 950-1000°C interval, and the interval below 800°C. In this case, the 950-1000°C interval is determined to be the highest temperature interval.

[0036] It is understandable that, due to the different sintering operating parameters of each sintering plant within a certain sintering cycle (e.g., different raw material conditions, gas conditions, and equipment models and specifications), it is impossible to quantitatively give a linear relationship between the current sintering critical temperature range and the current sintering section full cross-sectional range that is suitable for all sintering plants. The present invention establishes a return ore prediction model, establishes a corresponding relationship between the current raw material area ratio, the current sintering operating parameters, and the current sintering return ore rate, and can accurately predict the current sintering return ore rate of the current batch of trolleys based on the actual effective tail sintering section thermal imaging. It is understandable that the current batch of trolleys can be one sintering trolley or multiple sintering trolleys.

[0037] Furthermore, the area of ​​the current sintering critical temperature interval in the entire cross-sectional interval of the current sintering section and the area above the current sintering critical temperature interval are determined as the current sintering clinker interval; the current clinker area proportion of the current sintering clinker interval is obtained according to the ratio of the current sintering clinker interval to the current sintering critical temperature interval, the current raw material area proportion is determined according to the current clinker area proportion, and the sum of the current raw material area proportion and the current clinker area proportion is 1. Specifically, the current clinker area proportion is obtained according to the current sintering clinker interval and the current sintering critical temperature interval, and the sum of the current clinker area proportion and the current raw material area proportion is 1.

[0038] Furthermore, the bottom material interval of the current batch of trolleys is obtained based on the actual effective tail sintering section thermal imaging, and the bottom material interval is the space occupied by the actual bottom material on the bottom surface of the current batch of trolleys; the area between the current sintering critical temperature interval and the bottom material interval in the current sintering section full section interval is determined as the current sintering raw material section interval; the current raw material area ratio is obtained based on the ratio of the current sintering raw material section interval and the current sintering section full section interval.

[0039] Understandably, please refer to Figure 4 , analysis shows that the actual effective tail sintering section thermal imaging usually includes the current sintering section interval, the base material interval and the current sintering critical temperature interval. The sintering materials in the current sintering critical temperature interval and the base material interval are sintering raw materials (the actual combustion zone does not burn to the base material interval position before reaching the sintering end point), and the sintering materials in the current sintering critical temperature interval and the sintering materials above the current sintering critical temperature interval are sintering clinker. In the present invention, the current raw material area ratio is obtained by the current sintering clinker interval and the current sintering critical temperature interval, or the current raw material area ratio is obtained by the current sintering raw material section interval and the current sintering critical temperature interval; wherein, the current sintering raw material section interval, the current sintering clinker interval and the base material interval are combined to form the current sintering section interval.

[0040] Furthermore, based on the study of sintering, the ideal sintering thermal imaging of the current batch of trolleys is obtained, and the ideal sintering thermal imaging includes a theoretical paving layer; the ideal sintering thermal imaging and the actual effective tail sintering cross-section thermal imaging are integrated to determine the bottom material paving interval based on the theoretical paving layer.

[0041] Furthermore, the step of obtaining the highest temperature interval of the actual effective tail sintering cross-section thermal imaging is also included. If the temperature range value of the highest temperature interval is not less than the preset temperature range value, the highest temperature interval is determined to be the current sintering critical temperature interval. Optionally, the temperature value of the preset temperature range value is pre-set. If the sintering trolley material of the sintering trolley has been sintered before the tailmost bellows position, the sintered material will undergo a cooling walking process after being completely sintered. At this time, the temperature of the current sintering critical temperature interval will be lower than 1280°C; if the sintering trolley material of the sintering trolley is sintered at the tailmost bellows position, the temperature of the current sintering critical temperature interval will be around 1250°C (1230°C to 1280°C). At this time, the sintering material below the current sintering critical temperature interval is raw material.

[0042] Preferably, if the sintering cart fails to ignite, the sintering material has not yet been sintered. In this case, the current critical sintering temperature range is the entire sintering cross-section, and the thermal imaging temperature of the entire sintering cross-section will be below 600°C. To improve prediction accuracy, sintering carts that have not yet sintered are excluded, and the preset temperature range is 600°C to 1280°C. More preferably, the preset temperature range is 1000°C to 1280°C.

[0043] More preferably, in order to further improve the accuracy of the prediction, the temperature range of the current sintering critical temperature interval is 1250°C to 1280°C.

[0044] Furthermore, the historical sintering operating condition parameters include historical sintering air volume parameters, historical trolley speed parameters, and historical sintering material layer thickness parameters.

[0045] Furthermore, in order to improve the prediction accuracy, step S10 specifically includes: obtaining the initial actual sintering cross-sectional thermal imaging image of each target sintering trolley corresponding to the current batch of trolleys; filtering out the distorted initial actual sintering cross-sectional thermal imaging image; performing image processing on the initial actual sintering cross-sectional thermal imaging image after filtering out the distortion; overlapping and averaging the initial actual sintering cross-sectional thermal imaging image after image processing to obtain the actual effective tail sintering cross-sectional thermal imaging of the current batch of trolleys.

[0046] Furthermore, the sintering trolleys that pass through the sintering machine within the target time period are determined as the trolleys of the current batch. Specifically, the trolleys of the current batch are determined according to actual needs.

[0047] More preferably, the target time period is determined based on the actual operation of each trolley in the environmental machine.

[0048] Furthermore, if the current sintering return rate is greater than the return threshold, an early warning prompt is issued. It is understandable that the return threshold can be set according to actual conditions, and can be 20%, 10%, or other data.

[0049] Please refer to Figure 5 The present invention also provides an online sintering return rate prediction system based on machine tail section thermal imaging, which includes a sintering machine, a sintering trolley, a thermal imaging acquisition device and a processing device. The sintering trolley is movably arranged along the sintering machine head wheel toward the sintering machine tail wheel. The sintering machine is provided with a distribution area, an ignition furnace area and an insulation furnace area in sequence at one end close to the sintering machine head wheel; the thermal imaging acquisition device is arranged on the outside of the sintering machine tail wheel of the sintering machine, and the thermal imaging acquisition device is used to obtain the actual effective machine tail sintering section thermal imaging of the current batch of trolleys; the processing device is used to execute the steps of the above-mentioned online sintering return rate prediction method based on machine tail section thermal imaging.

[0050] As can be understood, a sensor is installed on the sintering machine's tail wheel to track the trolley's inclination angle A. When the trolley reaches inclination angle A, a thermal imaging camera captures the sintering machine's tail section to obtain the actual effective tail section thermal image. In this embodiment, an ideal sintering cross-section thermal image is obtained at the target sintering endpoint when the trolley inclination angle A is set, and the ideal sintering thermal image of the current batch of trolleys is obtained. The ideal sintering thermal image includes a theoretical paving layer. The ideal sintering thermal image and the actual effective tail section thermal image are combined to determine the bottom material paving interval based on the theoretical paving layer. The ideal temperature distribution diagram of the ideal sintering cross-section thermal image can be modeled by theoretical calculation. Specifically, a typical large-scale sintering machine trolley is 2 meters long and 5.5 meters wide, and the sintering trolley travels at a speed of 2 meters / min. When the tail wheel and trolley of the tail sintering machine tilt to a certain angle, the entire trolley's material slides to the downstream process, exposing the sintering cross-section of the trolley adjacent to the sliding material trolley. The system then obtains the tail section thermal image at this location.

[0051] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for predicting the online sintering return rate based on thermal imaging of the tail section of a machine, characterized in that: The steps include: S10, obtaining an actual effective tail sintering cross-section thermal image of the current batch of trolleys, wherein the actual effective tail sintering cross-section thermal image has a known correlation ratio with the real cross-section image of the current batch of trolleys; S20, obtaining a current sintering cross-section interval and a current sintering critical temperature interval of the trolley sintering material of the current batch of trolleys based on the actual effective tail sintering cross-section thermal image, wherein the temperature range of the current sintering critical temperature interval is 600° C. to 1280° C., and the current sintering critical temperature interval is within the current sintering cross-section interval; S30, calculating and obtaining a current raw material area ratio of a current sintering raw material interval according to a ratio of the current sintering critical temperature interval to the current sintering cross-section entire cross-sectional interval; S40, inputting the current raw meal area ratio and the current sintering operating condition parameters into a return ore prediction model to predict the current sintering return ore rate of the current batch of trolleys, wherein the historical sintering raw meal area ratio and the historical sintering operating condition parameters are used as a training input set, and the historical machine tail raw meal return ore rate is used as a training output set to establish the return ore prediction model through neural network learning; The historical sintering operating condition parameters include historical sintering air volume parameters, historical trolley speed parameters, and historical sintering material layer thickness parameters.

2. The method for predicting the online sintering return rate based on tail section thermal imaging according to claim 1 is characterized in that: Determine the area of ​​the current sintering critical temperature range and the area above the current sintering critical temperature range in the entire cross-sectional area of ​​the current sintering section as the current sintering clinker range; The current clinker area ratio of the current sintering clinker interval is obtained according to the ratio of the current sintering clinker interval to the current sintering critical temperature interval, and the current raw material area ratio is determined according to the current clinker area ratio. The sum of the current raw material area ratio and the current clinker area ratio is 1.

3. The method for predicting the online sintering return rate based on tail section thermal imaging according to claim 1 is characterized in that: Also includes the steps: Obtaining the bottom material paving interval of the current batch of trolleys based on the actual effective tail sintering cross-section thermal imaging, where the bottom material paving interval is the space actually occupied by the bottom material on the bottom surface of the current batch of trolleys; Determine the area between the current sintering critical temperature interval and the base material interval in the entire cross-sectional interval of the current sintering section as the current sintering raw material cross-sectional interval; The current raw material area ratio is obtained according to the ratio of the current sintering raw material cross-sectional interval to the current sintering cross-sectional entire cross-sectional interval.

4. The method for predicting the online sintering return rate based on tail section thermal imaging according to claim 3 is characterized in that: Acquire an ideal sintering thermal image of the current batch of trolleys, wherein the ideal sintering thermal image includes a theoretical paving layer; The ideal sintering thermal image and the actual effective tail sintering cross-section thermal image are integrated to determine the bottom material paving interval according to the theoretical paving layer.

5. The method for predicting the online sintering return rate based on tail section thermal imaging according to any one of claims 1 to 4, characterized in that: Also includes the steps: The highest temperature interval of the actual effective tail sintering cross-section thermal imaging is obtained. If the temperature range value of the highest temperature interval is not less than the preset temperature range value, the highest temperature interval is determined to be the current sintering critical temperature interval.

6. The method for predicting the online sintering return rate based on tail section thermal imaging according to any one of claims 1 to 4, characterized in that: Step S10 specifically includes: Acquire an initial actual sintering cross-sectional thermal imaging image of each target sintering trolley corresponding to the current batch of trolleys; filtering out the distorted initial actual sintered cross-section thermal imaging image; Performing image processing on the initial actual sintered cross-section thermal imaging image after filtering out distortion; The initial actual sintering cross-section thermal imaging image after image processing is overlapped and averaged for secondary processing to obtain the actual effective tail sintering cross-section thermal imaging of the current batch of trolleys.

7. The method for predicting the online sintering return rate based on tail section thermal imaging according to any one of claims 1 to 4, characterized in that: All sintering trolleys that pass through the sintering machine within the target time period are determined to be the trolleys of the current batch.

8. The method for predicting the online sintering return rate based on tail section thermal imaging according to any one of claims 1 to 4, characterized in that: If the current sintering return rate is greater than the return threshold, an early warning prompt is issued.

9. An online sintering return rate prediction system based on tail section thermal imaging, characterized by: The invention comprises a sintering machine, a sintering trolley, a thermal imaging acquisition device and a processing device. The sintering trolley is movably arranged along the sintering machine head wheel toward the sintering machine tail wheel. The sintering machine is provided with a material distribution area, an ignition furnace area and a holding furnace area in sequence at one end close to the sintering machine head wheel. The thermal imaging acquisition device is arranged on the outside of the sintering machine tail wheel of the sintering machine, and is used to acquire the actual effective tail sintering cross-section thermal image of the current batch of trolleys; The processing device is used to execute the steps of the online sintering return rate prediction method based on tail section thermal imaging as described in any one of claims 1 to 8.

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