A hot-rolled slab heating furnace temperature setting method based on furnace area multi-parameter weight

Abstract

The application discloses a kind of based on furnace area multi-parameter weight hot-rolled slab heating furnace temperature setting method, comprising: obtaining furnace area index data;Based on the obtained furnace area index data, carry out furnace area index weight distribution, obtain the comprehensive weight corresponding to each index, and based on the comprehensive weight of each index, calculate the hot-rolled slab heating furnace setting temperature;According to the calculated setting temperature, set furnace area temperature, execute billet heating treatment process;And in the execution process of steel billet heating treatment process, real-time monitoring furnace temperature, according to the monitoring result, dynamically adjust furnace temperature.The hot-rolled slab heating furnace temperature setting method of the application has universality, is suitable for the heating furnace of multiple layout types, only needs to collect and analyze relevant key parameters, can obtain the furnace temperature parameter suitable for most steel billets in furnace, effectively improves the heating effect of heating furnace and plays unit capacity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of plate strip heat treatment, and in particular to a hot-rolled slab heating furnace temperature setting method based on furnace area multi-parameter weight. BACKGROUND

[0002] The incoming material of the plate strip hot-rolling process needs to have a high temperature requirement, and its temperature rising process highly depends on the hot-rolled slab heating furnace. As a key process linking the continuous casting and the hot-rolling two process links, whether the heating furnace temperature control is superior or not will directly affect the stability of the hot-rolling production. Influenced by factors such as heating furnace stacking, incoming temperature, outgoing temperature, and furnace charge variety, a single heating furnace temperature setting cannot meet the needs of high-strength and high-continuous hot-rolling production. The hot-rolled base material supplied under the fixed furnace temperature setting is prone to have heating effect differences among varieties and specifications. At the same time, the stacking differences will also induce heating effect differences among the same variety and the same specification. The above phenomena will all act on the hot-rolling process, causing the hot-rolled products to have thickness difference fluctuations and uneven performance product problems, and then continuously affecting the downstream processes such as cold rolling, continuous annealing, leveling, packaging, etc. Improving the heating furnace temperature setting precision and level is a problem that needs to be solved in the current plate strip production process.

[0003] In view of this problem, the industry has successively proposed a large number of solutions, mainly including upstream process adjustment method and furnace area temperature rising control method. The upstream process adjustment method mainly adjusts the casting speed of the upstream continuous casting unit or adjusts the production rhythm according to the steel variety characteristics, controls the feeding frequency of the upstream unit to the furnace area of the hot-rolling heating furnace, so as to adjust the stacking state and temperature state in the furnace. The furnace area temperature rising control method adjusts the temperature level of each section of the heating furnace through the heating furnace production plan arrangement and the furnace area parameter adjustment. However, the above methods still have different problems. The upstream process adjustment method can alleviate the production pressure of the heating furnace from the incoming material source, but the line speed reduction or the adjustment of the steel variety production plan will directly affect the line capacity. Although the furnace area temperature rising control method directly adjusts the heating furnace, the existing method is difficult to cope with the heating of the steel billet of multiple varieties and multiple specifications and the complex material stacking due to the limitation of the control logic. Therefore, it is urgent to provide a hot-rolling heating furnace temperature control method that can consider and balance the influence of multiple parameters in the furnace area. SUMMARY

[0004] The present application provides a hot-rolled slab heating furnace temperature setting method based on furnace area multi-parameter weight to solve the technical problem that the traditional furnace temperature setting cannot consider and balance the influence of multiple parameters in the furnace area.

[0005] To solve the above technical problems, the present application provides the following technical solutions:

[0006] In one aspect, the present application provides a hot rolling slab heating furnace temperature setting method based on multi-parameter weight of furnace area, which comprises:

[0007] Obtaining furnace area index data; wherein the furnace area index includes billet charging temperature, deviation value of actual temperature and target temperature of billet, spatial position of billet, billet thickness after passing through finishing rolling mill set, and steel grade;

[0008] Based on the obtained furnace area index data, performing weight distribution of furnace area index to obtain comprehensive weight corresponding to each index, and based on the comprehensive weight of each index, calculating the set temperature of hot rolling slab heating furnace;

[0009] Setting the furnace area temperature according to the calculated set temperature, and performing billet heating treatment process; and monitoring the furnace temperature in real time during the execution of the billet heating treatment process, and dynamically adjusting the furnace temperature according to the monitoring result.

[0010] Further, the obtaining of the furnace area index data comprises:

[0011] Obtaining the steel grade and model i of the billet to be transferred into the furnace area, the billet thickness H i , the billet width B i , the billet length L i , the charging temperature T input-i , and the target temperature T target-i .

[0012] Calibrating the spatial zero point of the furnace area with the center position of the furnace area, and sequentially feeding each billet to be transferred into the furnace area into the furnace area, and obtaining the spatial position coordinates (x i , y i , z i ) of the center point of the billet.

[0013] Starting the heaters at each level of the furnace area, and obtaining the actual temperature T real-j of the reference billet j according to the furnace temperature detection device, and calculating the deviation value ΔT dev-j of the actual temperature and the target temperature of the billet j.

[0014] According to the feedback data of the downstream hot finishing rolling mill set, obtaining the thickness H hr-i of the billet i after passing through the furnace area and the finishing rolling mill set, and obtaining the steel grade P i according to the rolling force evaluation of the finishing rolling mill set.

[0015] Further, the weight distribution of the furnace area index based on the obtained furnace area index data to obtain the comprehensive weight corresponding to each index, and the calculation of the set temperature of the hot rolling slab heating furnace based on the comprehensive weight of each index, comprises:

[0016] Dividing the hot rolling heating furnace into n furnace zones;

[0017] Setting the target furnace temperature initial matrix T of the kth furnace zone k = [T k-1 ,T k-2 ,T k-3 ,…,T k-s ]; Wherein T k-i is the i-th element in T k , i = 1, 2, 3, …, s, s is the total number of billets contained in the kth furnace zone;

[0018] Obtaining the billet original data matrix X k of the kth furnace zone

[0019]

[0020] Wherein, ΔT dev-i is the deviation value of the actual temperature and the target temperature of the billet i, η i is the percentage of the billet i to the shortest billet distance from the exit section length, H hr-i is the exit thickness of the billet i through the finishing rolling mill set, T input-i is the billet i inlet temperature, P i is the billet i steel grade, i = 1, 2, 3, …, s;

[0021] According to the billet original data matrix X k , rough set weight level analysis is carried out, and the rough set level corresponding to each furnace zone index data is determined according to the preset level division standard; and based on the rough set level corresponding to each furnace zone index data, the parameter rough set decision matrix Z k of the kth furnace zone is obtained:

[0022]

[0023] Wherein, z ij is the rough set level corresponding to the jth index data of the billet i, taking the value of 1-5, i = 1, 2, 3, …, s, j = 1, 2, 3, 4, 5;

[0024] Establishing a comprehensive weight matrix, and carrying out weight decision analysis and solving the comprehensive weight of each index of the mth billet in the kth furnace zone according to the subjective weight and objective weight combination of subjective and objective weight method:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] wherein, q mj is the comprehensive weight of the jth index of the mth block of billets; μ u is the subjective and objective weight emphasis coefficient corresponding to the u th block of billets, and its value is 0-1; h = 1, 2, 3, 4, 5;

[0031] Based on the comprehensive weight of each index, the set furnace temperature T UD-k of the kth section of the furnace zone is solved.

[0032]

[0033] wherein, q uh is the comprehensive weight of the hth index of the u th block of billets.

[0034] Further, the rough set weight level analysis is performed according to the billet original data matrix X k , and the rough set level corresponding to the index data of each furnace zone is determined according to the preset level division standard, including:

[0035] According to the percentage of the deviation value of the actual temperature of the billet and the target temperature to the difference between the target temperature and the actual temperature of the billet, the deviation value index is divided into five levels; wherein, when the percentage is 0%-20%, the rough set level is 1; when the percentage is 20%-40%, the rough set level is 2; when the percentage is 40%-60%, the rough set level is 3; when the percentage is 60%-80%, the rough set level is 4; and when the percentage is 80%-100%, the rough set level is 5.

[0036] According to the percentage of the distance between the billet center point and the exit section length to the shortest billet distance exit section length, the space position of the billet center point is divided into five levels; wherein, when the percentage is 0%-20%, the rough set level is 1; when the percentage is 20%-40%, the rough set level is 2; when the percentage is 40%-60%, the rough set level is 3; when the percentage is 60%-80%, the rough set level is 4; and when the percentage is 80%-100%, the rough set level is 5.

[0037] The thickness of the billet after the finishing rolling mill is divided into five levels; wherein, when the thickness value is 0-1.8mm, the rough set level is 1; when the thickness value is 1.8mm-3.0mm, the rough set level is 2; when the thickness value is 3.0mm-6.0mm, the rough set level is 3; when the thickness value is 6.0mm-12mm, the rough set level is 4; and when the thickness value is greater than 12mm, the rough set level is 5.

[0038] The furnace temperature is divided into five levels; wherein, when the temperature is less than 200℃, the corresponding rough set level is 1, when the temperature is 200℃-400℃, the corresponding rough set level is 2, when the temperature is 400℃-600℃, the corresponding rough set level is 3, when the temperature is 600℃-800℃, the corresponding rough set level is 4, and when the temperature is greater than 800℃, the corresponding rough set level is 5;

[0039] According to the steel grade, the yield strength is divided into five levels; wherein, when the yield strength is 200MPa-400MPa, the corresponding rough set level is 1, when the yield strength is 400MPa-600MPa, the corresponding rough set level is 2, when the yield strength is 600MPa-800MPa, the corresponding rough set level is 3, when the yield strength is 800MPa-1000MPa, the corresponding rough set level is 4, and when the yield strength is 1000MPa-1200MPa, the corresponding rough set level is 5.

[0040] Further, the billet i distance from the section length d i =L hf / 2-L i / 2-x i ; the shortest billet distance from the section length d max =L hf / 2-L max / 2-x max ; wherein, L hf is the length of the heating furnace zone, L i is the billet length, x i is the spatial position horizontal coordinate of the billet center point, L max is the maximum value of the billet length, and x max is the maximum value of the spatial position horizontal coordinate of the billet center point.

[0041] Further, the furnace zone temperature is set according to the calculated set temperature, and the billet heating treatment process is performed; and the furnace temperature is monitored in real time during the execution of the billet heating treatment process, and the furnace temperature is dynamically adjusted according to the monitoring result, including:

[0042] The furnace zone temperature is set according to the calculated set temperature, and the billet heating treatment process is performed;

[0043] During the execution of the billet heating treatment process, the temperature change of the reference billet j is monitored according to the furnace temperature detection device, and compared with the target temperature curve;

[0044] If the temperature difference value of the billet j course temperature and the corresponding moment of the target temperature rise curve is less than 20℃, it indicates that the furnace zone temperature control is effective, and this process can be executed for a long time;

[0045] If the temperature difference between the billet j temperature and the target temperature rise curve at the corresponding time is greater than 20℃ but less than 50℃, then the furnace zone parameters need to be dynamically fine-tuned, and adaptive operation adjustment is performed;

[0046] If the temperature difference between the billet j temperature and the target temperature rise curve at the corresponding time is greater than 50℃, then the set temperature needs to be recalculated, and a new set furnace temperature value is given according to the current furnace zone index data.

[0047] In still another aspect, the present application also provides an electronic device comprising a processor and a memory; wherein the memory has at least one instruction stored therein, which is loaded and executed by the processor to implement the above method.

[0048] In still another aspect, the present application also provides a computer-readable storage medium, wherein the storage medium has at least one instruction stored therein, which is loaded and executed by the processor to implement the above method.

[0049] The technical solutions provided by the present application have at least the following beneficial effects:

[0050] 1. Compared with the upstream process adjustment method, the present application does not need to adjust the upstream process, and the parameter variation will not affect the production of the upstream unit, so that the production capacity of the production line can be maximized.

[0051] 2. Compared with the furnace zone temperature rise control method, the present application comprehensively considers the influence relationship of multiple parameters in the furnace zone, and formulates a weight analysis scheme serving the whole system process of the hot rolling heating furnace, so that the optimal hot rolling heating furnace temperature setting can be realized while optimizing the furnace temperature setting mechanism in the furnace zone, and the influence of multiple parameters in the furnace zone is considered and weighed. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 is the principle diagram of the hot rolling slab heating furnace temperature setting method based on the multi-parameter weight of the furnace zone provided by the embodiments of the present application;

[0054] Figure 2 is the execution flowchart of the hot rolling slab heating furnace temperature setting method based on the multi-parameter weight of the furnace zone provided by the embodiments of the present application;

[0055] Figure 3 is the flowchart of the parameter acquisition of the key attributes of the furnace zone provided by the embodiments of the present application;

[0056] Figure 4 is a flowchart of decision analysis of furnace zone parameter weight provided by an embodiment of the present application;

[0057] Figure 5 is a flowchart of execution and monitoring of furnace zone temperature setting target provided by an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the objects, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0059] First Embodiment

[0060] The setting of the temperature of the heating furnace before hot rolling not only determines the effect of the current process, but also affects the overall productivity of the production line. In view of the fact that the traditional furnace temperature setting fails to take into account and balance the influence of various parameters in the furnace zone, the present embodiment comprehensively considers the influence of a series of parameters such as furnace zone parameters, slab parameters and slab spatial positions, extracts the key attributes of the heating furnace and performs global parameter weight analysis. According to the weight, the hot rolling heating furnace zone temperature is determined, and a further optimization-monitoring-adjustment method for setting the furnace temperature is given. Thus, a hot rolling slab heating furnace temperature setting method based on the multi-parameter weight of the furnace zone is provided, and the implementation principle of the method is as shown in Figure 1 . It includes the following three links: parameter acquisition of furnace zone key attributes; decision analysis of furnace zone parameter weight; and execution and monitoring of furnace zone temperature setting target.

[0061] Specifically, the execution flow of the method is as shown in Figure 2 , which includes the following steps:

[0062] S1, acquiring furnace zone index data;

[0063] The furnace zone indexes include the slab entry temperature, the deviation value of the actual temperature and the target temperature of the slab, the spatial position of the slab, the thickness of the slab at the exit of the finishing rolling mill and the grade of the steel grade.

[0064] Specifically, in the present embodiment, the implementation process of S1 is as shown in Figure 3 , which includes:

[0065] S11, according to the production line production plan and the product specification database, acquiring the slab variety and grade i of the slab to be transferred into the furnace zone, the slab size and shape (slab thickness H i , slab width B i , slab length L i ), entry temperature T input-i , target temperature T target-i ;

[0066] S12, calibrate the space zero point (0, 0, 0) of the furnace area at the center position of the furnace area, and sequentially put each billet to be turned into the furnace area into the furnace area, and obtain the spatial position (x i ,y i ,z i ) of the center point of the billet;

[0067] S13, start the furnace area heaters at each level, and obtain the real-time temperature T real-j of the reference billet j according to the furnace temperature detection device, and calculate the deviation value ΔT dev-j of the real-time temperature of the billet j from the target temperature;

[0068] S14, according to the feedback data of the downstream hot finishing rolling mill unit, obtain the thickness H hr-i of each billet i after heating in the furnace area through the finishing rolling mill unit outlet, and obtain the steel grade P i according to the rolling force evaluation of the finishing rolling mill unit.

[0069] S2, based on the obtained furnace area index data, perform furnace area index weight distribution to obtain the comprehensive weight corresponding to each index, and based on the comprehensive weight of each index, calculate the set temperature of the hot rolling slab heating furnace;

[0070] Specifically, in the present embodiment, the implementation process of S2 is as shown in Figure 4 , which includes:

[0071] S21, according to the deviation value ΔT dev-j of the actual temperature and the target temperature, the spatial position (x i ,y i ,z i ) of the center point of the billet, the thickness H hr-i of the billet i through the finishing rolling mill unit outlet, the entry temperature T input-i , and the steel grade P i and other key attribute indexes extracted by S1, perform hot rolling slab heating furnace area temperature evaluation index weight distribution, including:

[0072] S211, for the deviation value ΔT dev-j of the actual temperature and the target temperature, according to the percentage difference of the deviation value from the entry temperature T input-j and the target temperature T target-j of the billet j, divide it into 5 levels. Among them, 0%~20% corresponds to level 1, 20%~40% corresponds to level 2, 40%~60% corresponds to level 3, 60%~80% corresponds to level 4, and 80%~100% corresponds to level 5;

[0073] S212, for the spatial position (x i ,y i ,z i), according to the billet i distance from the exit section length

d i = L hf / 2 - L i / 2 - x i , (wherein, L hf is the heating furnace zone length)

d max = L hf / 2 - L max / 2 - x max , (wherein, L hf is the heating furnace zone length, L max is the maximum value of billet length, x max is the maximum value of the spatial position of the billet center point horizontal coordinate)

[0074] S213, for the billet i thickness H hr-i , according to the thickness value is divided into five levels. Among them, 0 ~ 1.8mm corresponds to rough set level 1, 1.8mm ~ 3.0mm corresponds to rough set level 2, 3.0mm ~ 6.0mm corresponds to rough set level 3, 6.0mm ~ 12mm corresponds to rough set level 4, greater than 12mm corresponds to rough set level 5;

[0075] S214, for the billet i charging temperature T input-i , according to the temperature level is divided into five levels. Among them, less than 200℃ corresponds to rough set level 1, 200℃ ~ 400℃ corresponds to rough set level 2, 400℃ ~ 600℃ corresponds to rough set level 3, 600℃ ~ 800℃ corresponds to rough set level 4, greater than 800℃ corresponds to rough set level 5;

[0076] S215, for the billet i grade P i , according to the yield strength is divided into five levels. Among them, 200MPa ~ 400MPa corresponds to rough set level 1, 400MPa ~ 600MPa corresponds to rough set level 2, 600MPa ~ 800MPa corresponds to rough set level 3, 800MPa ~ 1000MPa corresponds to rough set level 4, 1000MPa ~ 1200MPa corresponds to rough set level 5;

[0077] S22, the hot rolling heating furnace is divided into n furnace zones;

[0078] S23, set the target temperature initial matrix T k = [T k-1 , Tk-2 ,T k-3 ,…,T k-s ]; among which, T k-i For T k The i-th element in the equation, i = 1, 2, 3, ..., s, where s is the total number of steel billets contained in the k-th furnace section;

[0079] S24, perform parameter matching based on furnace area parameters and process data, and obtain the original billet data matrix X for the k-th furnace area. k :

[0080]

[0081] Where, ΔT dev-i η is the deviation between the actual temperature and the target temperature of billet i. i H represents the percentage of the billet's distance from the exit section to the shortest billet distance. hr-i T represents the thickness of the steel billet exiting the finishing mill. input-i Let P be the furnace inlet temperature of the steel billet. i Let i represent the steel grade of the billet, where i = 1, 2, 3, ..., s;

[0082] S25, based on the original billet data matrix X k Rough set weight level analysis is performed, and based on the rough set level corresponding to the index data of each furnace area, the parameter rough set decision matrix Z of the k-th furnace area is obtained. k :

[0083]

[0084] Among them, z ij Let be the rough set level corresponding to the j-th index data of billet i, with a value of 1 to 5, i = 1, 2, 3, ..., s, j = 1, 2, 3, 4, 5;

[0085] S26. Establish a comprehensive weight matrix, and perform weighted decision analysis using a subjective-objective weighting method that combines subjective and objective weights, and solve for the comprehensive weights of each index of the m-th billet in the k-th furnace section:

[0086]

[0087]

[0088]

[0089]

[0090]

[0091] Where, q mjThe comprehensive weight of the jth index of the mth steel billet; μ u The subjective weight emphasis coefficient corresponding to the u th steel billet, which is 0-1, input by the operator; h is the index number, h = 1, 2, 3, 4, 5;

[0092] S27, based on the comprehensive weight of each index, the set furnace temperature T UD-k of the k th furnace zone is solved.

[0093]

[0094] Wherein, q uh is the comprehensive weight of the h th index of the u th steel billet.

[0095] S3, set the furnace temperature according to the calculated set temperature, execute the billet heating treatment process; and monitor the furnace temperature in real time during the execution of the billet heating treatment process, and dynamically adjust the furnace temperature according to the monitoring result.

[0096] Specifically, in the embodiment, the implementation process of S3 is as shown in Figure 5 , which includes:

[0097] S31, according to the set furnace temperature T UD-1 , T UD-2 , …, T UD-n of each furnace zone solved by S27, set the furnace temperature, and execute the billet heating treatment process;

[0098] S32, during the execution of the billet heating treatment process, according to the furnace temperature detection device, monitor the temperature change of the reference billet j and compare it with the target temperature curve;

[0099] S33, if the temperature difference value of the billet j temperature T real-j (t) corresponding to the target temperature rise curve at the moment is less than 20℃, it indicates that the furnace temperature control is effective, and this process can be executed for a long time;

[0100] S34, if the temperature difference value of the billet j temperature T real-j (t) corresponding to the target temperature rise curve at the moment is greater than 20℃ but less than 50℃, then dynamic fine tuning of the furnace zone parameters is needed at this time, and adaptive operation adjustment is needed.

[0101] S35, if the temperature difference value of the billet j temperature T real-j (t) corresponding to the target temperature rise curve at the moment is greater than 50℃, then S2 needs to be executed again, and new set temperature value is given according to the current furnace zone index data.

[0102] In summary, the embodiment is directed to different furnace temperature control sections of the heating furnace, according to the steel billet variety, size, shape, entry temperature, target temperature, and other key attributes, and the real-time data of the key attributes are used for decision analysis. Through the decision matrix calculation of the rough set theory, the furnace temperature setting weight value of each steel billet is obtained, and the necessary furnace temperature of the corresponding section of the conventional steel billet is combined to set the comprehensive furnace temperature of all steel billets in the section. The method has universality and is suitable for heating furnaces of various layout types. Only the relevant key parameters need to be collected and analyzed, and the furnace temperature parameters suitable for heating most of the steel billets in the furnace can be obtained, which effectively improves the heating effect of the heating furnace and plays the unit capacity.

[0103] Second embodiment

[0104] The embodiment applies the method of the application to a certain steel plant heating furnace before hot rolling, thereby further illustrating the implementation process of the method of the application and proving the effectiveness of the method of the application, which includes the following steps:

[0105] S1, obtain the key attribute parameters of the furnace area, including the following steps:

[0106] S11, according to the production line production plan and product specification database, obtain the steel billet variety and grade of the steel billets to be transferred into the furnace area, i.e. USIBOR1500, USIBOR1500, SPHC-B, USIBOR1500, SPHC-B, the size and shape of the steel billet (steel billet thickness (230, 230, 240, 230, 240) (mm), steel billet width (1540, 1530, 1100, 1440, 1050) (mm), steel billet length (10959, 10950, 10423, 10960, 10424) (mm), entry temperature (644, 723, 512, 840, 681) (℃), target temperature (1225, 1220, 1243, 1228, 1254) (℃);

[0107] S12, calibrate the spatial zero point (0, 0, 0) of the furnace area at the center position of the furnace area, and sequentially put each steel billet to be transferred into the furnace area into the furnace area, and obtain the spatial position of the center point of the steel billet (-1580, 0, 115), (0, 0, 115), (1540, 0, 115), (-575, 0, 235), (550, 0, 235);

[0108] S13, start the heaters at each level of the furnace area, and according to the furnace temperature detection device, obtain the real-time temperature T real-j of the reference steel billet j, and calculate the deviation value ΔT dev-j of the real-time temperature of the steel billet j and the target temperature (75, 139, 336, 198, 86) (℃);

[0109] S14, Based on feedback data from the downstream hot finishing mill, obtain the thickness H of each steel billet i after furnace heating at the exit of the finishing mill. hr-i (10,10,5.4,10,5.4)(mm), and the steel grade is obtained based on the rolling capacity assessment of the finishing mill.

[0110] S2, Furnace Area Parameter Weighting Decision Analysis, the specific steps include:

[0111] S21, based on the deviation value ΔT between the actual temperature and the target temperature extracted from S1. dev-j Spatial position of the center point of the steel billet (x i ,y i ,z i The thickness H of the steel billet at the exit of the finishing mill hr-i Furnace temperature T input-i Steel grade P i The weights of key attribute indicators, such as the furnace zone temperature evaluation index of the hot-rolled slab heating furnace, are allocated accordingly.

[0112] S211, for the deviation value ΔT between the actual temperature and the target temperature. dev-j According to the deviation value as a percentage of the furnace entry temperature T of the steel billet j input-j and target temperature T target-j The percentage difference (13%, 28%, 46%, 51%, 15%) is divided into 5 levels (1, 2, 3, 3, 1). The specific level configuration scheme is as follows: 0%~20% corresponds to level 1, 20%~40% corresponds to level 2, 40%~60% corresponds to level 3, 60%~80% corresponds to level 4, and 80%~100% corresponds to level 5.

[0113] S212, regarding the spatial position (x) of the billet center point i ,y i ,z i According to the length of the billet i from the exit section [d] i =L hf / 2-L i / 2-x i , (where L) hf [Length of heating furnace zone] occupies the length of the shortest billet outlet section [d] max =L hf / 2-L max / 2-x max , (where L) hf L is the length of the heating furnace zone. max x represents the maximum value of the billet length. max The percentage η of the maximum value of the abscissa of the spatial position of the billet center point. i(42%, 55%, 46%, 53%, 71%) five levels are divided (3, 3, 3, 3, 4). The specific level configuration scheme is as follows: 0%~20% corresponds to rough set level 1, 20%~40% corresponds to rough set level 2, 40%~60% corresponds to rough set level 3, 60%~80% corresponds to rough set level 4, and 80%~100% corresponds to rough set level 5;

[0114] S213, the thickness H of the billet i at the outlet of the finishing rolling mill is obtained hr-i According to the thickness value, five levels (1, 1, 2, 2, 1) are divided. The specific level configuration scheme is as follows: 0~1.8mm corresponds to rough set level 1, 1.8mm~3.0mm corresponds to rough set level 2, 3.0mm~6.0mm corresponds to rough set level 3, 6.0mm~12mm corresponds to rough set level 4, and greater than 12mm corresponds to rough set level 5;

[0115] S214, the charging temperature T of the billet is obtained input-i According to the temperature level, five levels (4, 4, 3, 5, 4) are divided. The specific level configuration scheme is as follows: less than 200℃ corresponds to rough set level 1, 200℃~400℃ corresponds to rough set level 2, 400℃~600℃ corresponds to rough set level 3, 600℃~800℃ corresponds to rough set level 4, and greater than 800℃ corresponds to rough set level 5;

[0116] S215, the grade P of the steel grade is obtained i (1, 1, 3, 1, 3), five levels are divided according to the yield strength. The specific level configuration scheme is as follows: 200MPa~400MPa corresponds to rough set level 1, 400MPa~600MPa corresponds to rough set level 2, 600MPa~800MPa corresponds to rough set level 3, 800MPa~1000MPa corresponds to rough set level 4, and 1000MPa~1200MPa corresponds to rough set level 5;

[0117] S22, the hot rolling heating furnace is regarded as one furnace zone as a whole. The furnace zone includes five billets, and the initial matrix of the target furnace temperature is [1225, 1220, 1243, 1228, 1254];

[0118] S23, parameter matching is performed according to the furnace zone parameters and process data, and the original data matrix X of the billets in the furnace zone is obtained.

[0119]

[0120] S24, rough set weight level analysis is performed according to the original data matrix X of the billets, and the parameter rough set decision matrix Z of the furnace zone is obtained.

[0121]

[0122] S25, the comprehensive weight matrix is established, and the subjective weight and the objective weight are combined to perform the subjective and objective weighting method, and the first to fifth index comprehensive weight values q of the mth billet in the furnace area are solved m1 m2 m3 m4 m5 .

[0123] m1 = [0.0946 0.1526 0.2839 0.3643 0.1036] T

[0124] m2 = [0.1799 0.1455 0.1799 0.2317 0.2630] T

[0125] m3 = [0.1340 0.1089 0.2678 0.2678 0.1465] T

[0126] m4 = [0.1901 0.1541 0.1425 0.3052 0.2081] T

[0127] m5 = [0.1066 0.0862 0.3197 0.1372 0.3503] T

[0128] S26, based on the weight parameter, the set furnace temperature T of the furnace area is solved U

[0129] UD = 1235.69

[0130] S3, according to the set furnace temperature of the furnace area solved by S26, the billet heating treatment process is performed. When the temperature difference value of the temperature T real-i (t) corresponding to the target temperature rise curve is greater than 20℃ but less than 50℃, the dynamic fine adjustment of the furnace area parameter is performed at this time, the set temperature of the furnace area is fine adjusted by 30℃, and the billet heating treatment process is performed again. According to the furnace temperature detection device, the temperature change of the reference billet j is monitored and compared with the target temperature curve, and the temperature T real-j (t) corresponding to the target temperature rise curve is less than 20℃, which indicates that the furnace temperature control is effective, and the process can be executed for a long time.

[0131] Third embodiment​​​​​​​​​​

[0132] The embodiment provides an electronic device, including a processor and a memory; wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment.

[0133] The electronic device can be different in configuration or performance, and can include one or more processors (central processing units, CPUs) and one or more memories, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the above method.

[0134] The fourth embodiment

[0135] The embodiment provides a computer readable storage medium, which stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment. The computer readable storage medium can be a ROM, a random access memory, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc. The instruction stored therein can be loaded and executed by the processor in the terminal to implement the above method.

[0136] In addition, it should be noted that the present application can be provided as a method, device or computer program product. Therefore, the embodiments of the present application can be in the form of a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application can be in the form of a computer program product embodied on one or more computer usable storage media having computer usable program code.

[0137] The embodiments of the present application are described with reference to flowcharts and / or block diagrams of the method, terminal device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the computer or other programmable data processing terminal device produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The device for implementing the functions specified in one flow or multiple flows and / or blocks Figure 1 The device for implementing the functions specified in one flow or multiple flows and / or blocks

[0138] These computer program instructions can also be stored in a computer readable memory capable of guiding the computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer readable memory produce a product including instruction devices, which implement the functions specified in the flowchartsFigure 1 one or more processes and / or functions specified in the block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks. These computer program instructions can also be loaded into computer or other programmable data processing terminal devices to cause a series of operational steps to be performed on the computer or other programmable terminal devices to produce a computer implemented process so that the instructions which execute on the computer or other programmable terminal devices provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks. Figure 1 one or more processes and / or functions specified in the block or blocks.

[0139] It is also important to note that while the above describes example embodiments, there are several variations and modifications which can be made to these embodiments without departing from the spirit and scope of the application. For example, the order or sequence of any process steps can be varied or re-sequenced without departing from the scope of the application. Other steps can be performed or it can be decided to omit some steps. It is therefore contemplated to cover any and all modifications, variations or equivalents that fall with the scope of the present application. It is further noted that any processes, steps or techniques described herein can be performed by a suitable processor or controller, such as a computing device, a microprocessor, a microcontroller, a programmable logic device (PLD), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like, or a combination thereof.

[0140] Finally, it is to be noted that the above-described embodiments are merely exemplary of the application, and that it is intended to cover any and all modifications and variations of the preferred embodiments which fall within the scope of the application. It is therefore mature to include all such modifications and variations as fall within the scope of the inventive concepts. It is the scope of the claims and their equivalents that should be accorded broad coverage without limitation.

Claims

1. A method for setting a temperature of a hot rolling slab heating furnace based on a multi-parameter weight of a furnace zone, characterized in that, The hot-rolled slab heating furnace temperature setting method based on the furnace zone multi-parameter weight comprises: Obtaining furnace zone index data; wherein, the furnace zone indexes include slab charging temperature, deviation value of actual slab temperature and target temperature, slab spatial position, slab thickness after the finishing rolling mill and steel grade; Based on the obtained furnace zone index data, the furnace zone index weight distribution is performed to obtain the comprehensive weight corresponding to each index, and the hot-rolled slab heating furnace setting temperature is calculated based on the comprehensive weight of each index; including: Dividing the hot-rolled heating furnace into n furnace zones; Set the initial target furnace temperature matrix T for the k-th furnace zone. k =[T k-1 ,T k-2 ,T k-3 ,…,T k-s ]; among which, T k-i For T k The i-th element in the equation, i = 1, 2, 3, ..., s, where s is the total number of steel billets contained in the k-th furnace section; Obtaining the billet original data matrix X of the kth furnace zone k : wherein ΔT dev-i is the deviation value of the actual temperature of the billet i from the target temperature, η i is the percentage of the billet i distance from the exit section length to the shortest billet distance from the exit section length, H hr-i is the thickness of the billet i after the finishing rolling mill group, T input-i is the billet i entry temperature, P i is the billet i steel grade, i = 1, 2, 3, …, s; According to the billet original data matrix X k , rough set weight grade analysis is performed, and according to a preset grade division standard, rough set grades corresponding to the index data of each furnace zone are determined respectively; and based on the rough set grades corresponding to the index data of each furnace zone, a parameter rough set decision matrix Z k of the kth furnace zone is obtained: wherein z ij is the rough set level corresponding to the jth index data of the billet i, and takes a value of 1-5, i = 1, 2, 3, …, s, j = 1, 2, 3, 4, 5; Establishing a comprehensive weight matrix, and performing weighting decision analysis and solving the comprehensive weight of each index of the m slab in the k furnace zone according to the subjective weight and objective weight combined subjective and objective weighting method; wherein q mj is the comprehensive weight of the jth index of the mth steel billet; μ u is the subjective weight emphasis coefficient corresponding to the u th steel billet, and has a value of 0-1; h = 1, 2, 3, 4, 5; Based on the comprehensive weight of each index, solve the set furnace temperature T of the kth furnace zone UD-k : wherein q uh is the overall weight of the hth index of the u th steel billet; Setting the furnace zone temperature according to the calculated setting temperature, and executing the slab heating treatment process; and monitoring the furnace temperature in real time during the execution of the slab heating treatment process, and dynamically adjusting the furnace temperature according to the monitoring result.

2. The furnace zone multi-parameter weight-based hot rolling slab heating furnace temperature setting method according to claim 1, characterized in that, The obtaining of the furnace zone index data comprises: Obtain the steel billet variety grade i, steel billet thickness H of the steel billet to be transferred into the furnace area i , steel billet width B i , steel billet length L i , the temperature T of entering the furnace input-i And target temperature T target-i ; The spatial zero point of the furnace area is marked at the center of the furnace area, and each steel billet to be transferred into the furnace area is sequentially put into the furnace area, and the spatial coordinates (x, y, z) of the center point of the steel billet are obtained. i ,y i ,z i ); Start the heaters of the respective stages of the heating zone, and acquire the actual temperature T of the reference billet j based on the in-furnace temperature detecting device real-j , and calculate the deviation value ΔT of the actual temperature of the billet j from the target temperature dev-j ; According to the feedback data of the downstream hot finishing rolling mill group, the thickness H of the billet i after heating in the furnace area and passing through the finishing rolling mill group is obtained hr-i , and the steel grade P is obtained according to the rolling force evaluation of the finishing rolling mill group i .

3. The furnace zone multi-parameter weight-based hot rolling slab heating furnace temperature setting method according to claim 1, characterized in that, The original data matrix X of the steel billet k The rough set weight level analysis is performed, and the rough set level corresponding to the index data of each furnace area is determined according to the preset level division standard, including: According to the percentage of the deviation value of the actual slab temperature and the target temperature in the difference between the slab charging temperature and the target temperature, the deviation value index is divided into five levels; wherein, when the percentage is 0%-20%, the rough set level is 1; when the percentage is 20%-40%, the rough set level is 2; when the percentage is 40%-60%, the rough set level is 3; when the percentage is 60%-80%, the rough set level is 4; and when the percentage is 80%-100%, the rough set level is 5; According to the percentage of the slab distance from the exit section length to the shortest slab distance from the exit section length, the spatial position of the slab center point is divided into five levels; wherein, when the percentage is 0%-20%, the rough set level is 1; when the percentage is 20%-40%, the rough set level is 2; when the percentage is 40%-60%, the rough set level is 3; when the percentage is 60%-80%, the rough set level is 4; and when the percentage is 80%-100%, the rough set level is 5; The slab thickness after the finishing rolling mill is divided into five levels; wherein, when the thickness value is 0-1.8mm, the rough set level is 1; when the thickness value is 1.8mm-3.0mm, the rough set level is 2; when the thickness value is 3.0mm-6.0mm, the rough set level is 3; when the thickness value is 6.0mm-12mm, the rough set level is 4; and when the thickness value is greater than 12mm, the rough set level is 5; The charging temperature is divided into five levels; wherein, when the temperature is less than 200℃, the rough set level is 1; when the temperature is 200℃-400℃, the rough set level is 2; when the temperature is 400℃-600℃, the rough set level is 3; when the temperature is 600℃-800℃, the rough set level is 4; and when the temperature is greater than 800℃, the rough set level is 5; According to the yield strength, the steel grades are divided into five levels; when the yield strength is 200MPa-400MPa, the corresponding rough set level is 1, when the yield strength is 400MPa-600MPa, the corresponding rough set level is 2, when the yield strength is 600MPa-800MPa, the corresponding rough set level is 3, when the yield strength is 800MPa-1000MPa, the corresponding rough set level is 4, and when the yield strength is 1000MPa-1200MPa, the corresponding rough set level is 5.

4. The method for setting the temperature of a hot rolling slab heating furnace based on the multi-parameter weight of the furnace zone according to claim 3, characterized in that, billet i distance from the exit section length d i = L hf / 2 - L i / 2 - x i ; shortest billet distance from the exit section length d max = L hf / 2 - L max / 2 - x max ; wherein L hf is the length of the heating furnace zone, L i is the billet length, x i is the spatial position abscissa of the billet center point, L max is the maximum value of the billet length, x max is the maximum value of the spatial position abscissa of the billet center point.

5. The furnace zone multi-parameter weight-based hot rolling slab heating furnace temperature setting method according to claim 1, characterized in that, The furnace zone temperature is set according to the calculated set temperature, and the billet heating treatment process is performed; And in the process of steel billet heating treatment process, the furnace temperature is monitored in real time, and the furnace temperature is dynamically adjusted according to the monitoring results, including: The furnace zone temperature is set according to the calculated set temperature, and the billet heating treatment process is performed; In the process of steel billet heating treatment process, the temperature change of the reference billet j is monitored according to the furnace temperature detection device, and compared with the target temperature curve; If the temperature difference between the temperature of the steel billet j and the corresponding time of the target temperature curve is less than 20℃, it indicates that the furnace zone temperature control is effective, and the process can be executed for a long time; If the temperature difference between the temperature of the steel billet j and the corresponding time of the target temperature curve is greater than 20℃ but less than 50℃, then the furnace zone parameters need to be dynamically fine-tuned and adaptive operation adjustment is needed; If the temperature difference between the temperature of the steel billet j and the corresponding time of the target temperature curve is greater than 50℃, the set temperature needs to be recalculated, and a new set furnace temperature value is given according to the current furnace zone index data.

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