Online sintering return mine rate prediction method and system based on tail section thermal imaging

Abstract

The invention discloses an online sintering return mine rate prediction method and system based on tail section thermal imaging. The online sintering return mine rate prediction method comprises the following steps that the actual effective tail sintering section thermal imaging of a current batch of trolleys is obtained; obtaining a current sintering section whole section interval and a current sintering critical temperature interval of trolley sintering materials of the current batch of trolleys according to the actual effective machine tail sintering section thermal imaging; according to the ratio of the current sintering critical temperature interval to the current sintering section whole section interval, the current raw material area proportion of the current sintering raw material interval is obtained through calculation; and inputting the current raw material area proportion and the current sintering working condition parameters into a return mine prediction model to predict the current sintering return mine rate of the current batch of trolleys. According to the online sintering return ore rate prediction method based on tail section thermal imaging, the sintering return ore rate is obtained in real time, and the technical problems that in the prior art, the sintering return ore rate needs to be obtained after screening and weighing, the sintering working condition cannot be adjusted in time according to the sintering return ore rate, and the sintering efficiency is low are solved.

Description

Technical Field

[0001] The invention relates to the technical field of sintering, 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 getting larger and larger, and energy consumption is also increasing. Energy conservation and environmental protection indicators are becoming more and more important factors to consider in the steel production process. In steel production, iron-containing raw ore needs to be processed by the sintering system before entering the blast furnace for smelting. That is, various powdered iron-containing raw materials are mixed with appropriate amounts of fuel (coal powder, coke powder) and flux, and appropriate amounts of water. After mixing and balling, they are placed on the sintering trolley for roasting, so that a series of physical and chemical changes occur, forming sintered ore that is easy to smelt. This process is called sintering.

[0003] The sintering process includes ignition sintering, crushing, cooling with an annular cooler, and screening, wherein the screened material after screening is the sintered finished ore, and the screened material after screening is the sintered return ore. In the prior art, the sintering return rate is obtained by weighing the weight of the screened material and the screened material. Since the sintering machine has a long working time in the annular cooler cooling, the sintering return rate cannot be predicted in time after the sintering machine completes sintering, resulting in a serious lag in obtaining the sintering return rate, and the sintering conditions cannot be adjusted in time according to the sintering return 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 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 time and low sintering efficiency.

[0006] To achieve the above purpose, 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 section thermal image of the current batch of trolleys, and the actual effective tail sintering section thermal image has a known correlation ratio with the real cross-sectional image of the current batch of trolleys; S20, obtain 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 sintering section thermal image, the temperature range of the current sintering critical temperature interval is 600℃ to 1280℃, and the current sintering critical temperature interval is located within the current sintering section full section interval; S30, calculate the current raw material area ratio of the current sintering raw material interval according to the ratio of the current sintering critical temperature interval and the current sintering section full section interval; S40, input the current raw material area ratio 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 ratio 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 the 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 to 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, the steps are also included: 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 entire 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 entire section interval.

[0011] Furthermore, 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, and the bottom material paving interval is determined according to the theoretical paving layer.

[0012] Furthermore, the method also 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 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; performing secondary processing imaging by 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 machine tail section thermal imaging, comprising 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, and the sintering machine is provided with a 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 outer side 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.

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

[0017] The online sintering return rate prediction method and system based on tail section thermal imaging provided by the present invention are based on the research on sintering technology, and timely obtain 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 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 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 condition according to the sintering return rate in time, and the technical problem of low sintering efficiency.

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

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

[0020] Figure 1It 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 It is a flow chart of the method for predicting the online sintering return rate based on the thermal imaging of the tail section 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 schematic diagram of an 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 used to limit the present invention.

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[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 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 only used for descriptive purposes and cannot 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" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a 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 in the figure: various raw materials are proportioned in the batching room to form a mixture. After the mixture enters the mixer for mixing and balling, it is evenly spread on the sintering trolley through the round roller feeder and the nine-roller distributor to form a sintering mixture layer. The ignition fan and the ignition fan start the ignition furnace, and the sintering mixture on the top layer of the sintering trolley is ignited in the ignition furnace. 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 then cooled in an annular cooler. Finally, it is sent to the blast furnace or the finished ore bin after screening and granulation. Among them, the oxygen required for the sintering process is provided by the main exhaust fan. There are multiple vertically arranged bellows under the sintering trolley. Under the bellows is a horizontally placed large flue (or flue). The large flue is connected to the main exhaust fan. The negative pressure wind generated by the main exhaust fan through the large flue and the bellows passes through the trolley to provide combustion-supporting 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. It is difficult to distinguish the proportion of clinker return ore and raw meal return ore in time at the tail of the sintering machine with the existing technology.

[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) of the sintering machine, 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 mixed material 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 a bottom material layer, a mixed material layer, a combustion zone layer, and a 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 is high, and the sintering efficiency is high. Optionally, if the bottom of the combustion zone does not touch the bed material layer when reaching the first to last bellows, raw meal is produced between the bottom of the combustion zone and the bed material layer.

[0031] Please refer to Figure 1 and Figure 2 Through the study of sintering technology, it is found that the formation process of sintered ore 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 mixed materials in the combustion zone are roasted at high temperature to form sintered ore. After the combustion zone gradually moves down to the bottom of the sintering trolley to lay the bottom material layer, the combustion zone will no longer move down, and the fuel in the combustion zone has been burned. Among them, during the gradual downward movement of the combustion zone, the sintering machine trolley is also moving towards the direction of 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-roll 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 returned ore; the more returned ore, the more unfavorable it is for sintering production. For example, if the sintering machine outlet material is 100% and the returned ore is 20%, then the sintered product is only 80% of the sintering outlet material. If the returned ore is 5%, the product has the sintering outlet material. 95%, the lower the return rate, the higher the utilization rate of the sintering machine; there are raw material return and clinker return in the sintering return. Raw material return means that part of the mixed material on the sintering trolley has not entered the sintering process, and the mixed material has not been roasted into sintered ore. It will become powder in the sintering cooling and other links. Most of these powder materials will be screened out in the screening link (for example, particle size <3mm), which is raw material return; clinker return means that some sintered ores are broken into powder due to friction, falling in the feeding link and other factors in the process from the sintering machine to the screening, and will also be screened out in the screening link; the main reason for the formation of raw material return is that the mixed material 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 the return of raw material and the return of clinker, 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 sintering section thermal imaging of the current batch of trolleys, the actual effective tail sintering section thermal imaging and the real cross-sectional image of the current batch of trolleys have a known correlation ratio; S20, according to the actual effective tail sintering section thermal imaging, 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, the temperature range value of the current sintering critical temperature interval is 600°C to 1280°C, and the current sintering 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 according to 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, and timely obtains the actual effective tail sintering cross-section thermal imaging from the tail wheel position of the sintering machine. The actual effective tail sintering cross-section thermal imaging has a known correlation ratio with the real cross-sectional image of the current batch of trolleys. The current sintering cross-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 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 condition according to the sintering return rate in time, and the technical problem of low sintering efficiency.

[0035] It can be understood that thermal imaging technology belongs to the prior art, and through thermal imaging technology, the thermal imaging temperature partition interval of the actual effective tail sintering section thermal imaging can be obtained. Optionally, the temperature range value 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 thermal imaging. For example, the thermal imaging accuracy is divided into a level every 50°C, and the actual effective tail sintering section thermal imaging has an 800-850°C interval, an 850-900°C interval, a 900-950°C interval, a 950-1000°C interval, and an interval below 800°C. At this time, the 950-1000°C interval is determined to be the highest temperature interval.

[0036] It is understandable that, due to the different sintering parameters of each sintering plant in a certain sintering cycle (e.g., different raw material conditions, gas conditions, equipment models and specifications), it is impossible to quantitatively give a linear relationship between the current sintering critical temperature interval and the current sintering section entire section interval that is suitable for all sintering plants. The present invention establishes a return ore prediction model, establishes the corresponding relationship between the current raw material area ratio, the current sintering 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] Further, 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 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, and the sum of the current raw material area ratio and the current clinker area ratio is 1. Specifically, the current clinker area ratio is obtained according to the current sintering clinker interval and the current sintering critical temperature interval, and the sum of the current clinker area ratio and the current raw material area ratio 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 entire 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 entire 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 has not burned to the base material interval 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 clinkers. 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, it also 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, then determining the highest temperature interval as the current sintering critical temperature interval. Optionally, the temperature value of the preset temperature range value is pre-set, and if the trolley material of the sintering trolley has completed sintering before the most tail bellows position, the sintered material will go through a cooling walking process after being completely sintered, and the temperature of the current sintering critical temperature interval will be lower than 1280°C; if the trolley material of the sintering trolley completes sintering at the most tail bellows position, the temperature of the current sintering critical temperature interval will be around 1250°C (1230°C to 1280°C), and at this time, the sintering material below the current sintering critical temperature interval is raw material.

[0042] Preferably, if the sintering trolley fails to ignite, the sintering material has not been sintered. At this time, the current critical sintering temperature range is the entire sintering section range, and the thermal imaging temperature of the entire sintering section range will be lower than 600°C. In order to improve the prediction accuracy, the sintering trolleys that have not been sintered are eliminated, and the preset temperature range value is 600°C to 1280°C. More preferably, the preset temperature range value 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; performing secondary processing on the initial actual sintering cross-sectional thermal imaging image after image processing by overlapping and averaging, and obtaining the actual effective tail sintering cross-sectional thermal imaging of the current batch of trolleys.

[0046] Further, the sintering trolleys passing through the sintering machine within the target time period are determined as the current batch trolleys. Specifically, the current batch trolleys 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 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, including 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, and the sintering machine is provided with a distribution area, an ignition furnace area and a holding furnace area in sequence at one end of the sintering machine close to the sintering machine head wheel; the thermal imaging acquisition device is arranged on the outer side 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] It can be understood that a sensor is installed on the tail wheel of the sintering machine to track the inclination angle A of the trolley. When the inclination angle A of the trolley is reached, the thermal imaging camera takes a picture of the tail section of the sintering machine to obtain the actual effective thermal imaging of the tail sintering section. In this embodiment, the ideal sintering section thermal imaging at the target sintering end position when the trolley inclination angle A is set, and the ideal sintering thermal imaging of the current batch of trolleys is obtained. The ideal sintering thermal imaging includes a theoretical paving layer; the ideal sintering thermal imaging and the actual effective tail sintering section thermal imaging are integrated, and the bottom material paving interval is determined according to the theoretical paving layer. The ideal temperature distribution diagram of the ideal sintering section thermal imaging can be determined by theoretical calculation. Model. Specifically, the length of a typical large sintering machine trolley is 2 meters, the width is 5.5 meters, and the travel speed of the sintering trolley is 2 meters / min; after the tail wheel belt trolley of the tail sintering machine is tilted to a certain angle, the material of the entire trolley slides to the downstream process, and the sintering section of the trolley adjacent to the sliding material trolley is exposed, and the system obtains the thermal imaging of the tail section here.

[0051] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for predicting the online sintering return rate based on thermal imaging of the tail section, characterized in that: The steps include: S10, obtaining the 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 the current sintering section entire 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 section thermal imaging, wherein the temperature range value 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 section entire section interval; S30, calculating and obtaining the current raw material area ratio of the current sintering raw material interval according to the ratio of the current sintering critical temperature interval to the current sintering cross-section entire cross-sectional interval; S40, inputting the current raw material area ratio and the current sintering condition 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 ratio and the historical sintering condition parameters are used as training input sets, and the historical machine tail raw material return ore rate is used as the training output set to establish the return ore prediction model through neural network learning.

2. The method for predicting the online sintering return rate based on the thermal imaging of the tail section of claim 1 is characterized in that: Determine the area of ​​the current sintering critical temperature interval and the area above the current sintering critical temperature interval in the entire cross-sectional area of ​​the current sintering section as the current sintering clinker interval; 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, and 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 the thermal imaging of the tail section of claim 1 is characterized in that: Also includes the steps: Acquire the bottom material paving interval of the current batch of trolleys according to the actual effective tail sintering section thermal imaging, wherein the bottom material paving interval is the space occupied by the actual bottom material paving 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 the thermal imaging of the tail section of claim 3 is characterized in that: Acquire the 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 imaging and the actual effective tail sintering cross-section thermal imaging 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 the thermal imaging of the tail section of any one of claims 1 to 4, characterized in that: Also includes the steps: The highest temperature interval of the actual effective tail sintering section thermal imaging is obtained, and 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 online sintering return rate based on tail section thermal imaging according to any one of claims 1 to 4, characterized in that: The historical sintering condition parameters include historical sintering air volume parameters, historical trolley speed parameters and historical sintering material layer thickness parameters.

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: Step S10 specifically includes: Acquire an initial actual sintering cross-section 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; Processing 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.

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

9. 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.

10. An online sintering return rate prediction system based on tail section thermal imaging, characterized in that: It 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 material distribution area, an ignition furnace area and a heat preservation furnace area in sequence at one end close to the sintering machine head wheel. The thermal imaging acquisition device is arranged on the outer side of the sintering machine tail wheel of the sintering machine, and the thermal imaging acquisition device is used to acquire the actual effective tail sintering section thermal imaging 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 9.

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