Intelligent steel burning method for wide and thick plate heating furnace

Abstract

The invention discloses an intelligent steel burning method for a wide and thick plate heating furnace, and belongs to the field of thick plate rolled steel production. The method comprises the steps of determining the target slab tapping temperature of the thick plate heating furnace, determining the tail temperature of each section of the slab, determining the minimum in-furnace time of the slab, calculating a residual in-furnace time calculation model, calculating the in-furnace and in-section time of the slab, optimally calculating the set temperature of the heating furnace, optimizing the rest treatment strategy of the heating furnace, and setting a model of an excess air coefficient. The method disclosed by the invention can effectively improve the steel burning automation rate of the heating furnace by about 20%, and has positive significance in reducing the workload of operators and improving the field operation efficiency. And meanwhile, by accurately controlling the heating temperature of the plate blank, the tapping temperature hit rate of the plate blank can be effectively increased, and a certain effect on improving the heating quality of the plate blank is achieved. And through slab heating temperature control, the burnup of the heating furnace can be properly reduced, and the slab heating cost is reduced.

Description

Technical Field

[0001] The invention relates to thick plate steel rolling production, and in particular to a method for intelligent steel burning in a wide and thick plate heating furnace. Background Art

[0002] In the thick plate rolling production process, the heating of the raw material slab is mainly completed by continuous step-beam or push-steel heating furnaces. The heating target of the slab is generally the minimum furnace time of the slab and the average temperature of the slab at the furnace exit point, so as to ensure the uniformity of slab heating and the complete austenitization of the material and the solid solution requirements of alloy elements. For each steel mill, the fuel consumption of slab heating is an important cost indicator. Generally, the annual fuel consumption cost of a rolling mill with an annual output of 1 million tons can reach more than 80 million yuan. Therefore, energy saving and consumption reduction in the slab heating process has always been a work that steel companies need to continuously improve.

[0003] Due to the diversity of slab materials, rolling specifications, and the differences in the temperature of hot-charged slabs entering the furnace, the slabs' furnace time and heating temperature (heating curve) are also different. When slabs with different heating requirements are continuously loaded into the furnace for production, the difficulty of temperature control in each section of the heating furnace increases. The slab heating temperature is positively correlated with fuel consumption. Under the condition of meeting the stable rhythm of slabs leaving the furnace, it is very critical to complete the heating of the slabs at various positions in the furnace with the minimum heating temperature setting. In addition, in the actual production process, the rhythm of slab steelmaking has been changing dynamically, and the furnace temperature setting also needs to be adjusted accordingly in a timely manner.

[0004] The target and setting requirements for heating the slab temperature are dynamically related to the position and movement speed in the furnace. To reduce fuel consumption, dynamic adjustment and correction of the temperature setting are required. In terms of slab heating in domestic thick plate mills, employees mainly control the temperature setting of each section of the furnace based on the requirements of the time of leaving the furnace, and regularly track and dynamically adjust it for a long time, which is highly dependent on the energy and experience of the operators. There are many factors to consider when setting the temperature, including variety, specification, rhythm prediction, and different heating requirements for different varieties in the same section of the furnace. It is difficult to achieve unified requirements, and it also poses a great challenge to realize automatic steel burning in the heating furnace.

[0005] At present, due to factors such as slab specifications, processes and slab charging temperature, the slab time in the furnace and heating temperature (heating curve) are also different. When slabs with different heating requirements are continuously charged into the furnace for production, the temperature control of each section of the heating furnace becomes more difficult. Affected by the changes in the rolling rhythm, the operator needs to adaptively adjust the temperature in the furnace to ensure that the temperature of each section of the slab and the temperature out of the furnace meet the production requirements. Due to the different rolling rhythms of slabs of different steel grades, the temperature in the furnace needs to be adjusted multiple times. Due to the requirements of steel plate rolling quality, the slab heating temperature needs to be adjusted in combination with the rolling state of the rolling mill to ensure the normal rolling of the rolling mill and meet the steel plate rolling quality. Summary of the invention

[0006] Purpose of the invention: The purpose of the present invention is to provide a method for intelligent steel burning in a wide and thick plate heating furnace.

[0007] Technical solution: A method for intelligent steel burning in a wide and thick plate heating furnace, comprising:

[0008] ① Determination of target temperature of slab out of furnace

[0009] According to the target temperature requirements of the rolling plan issued by L3, the special steel slabs are adjusted according to the rolling line requirements, and the priority is determined according to different requirement levels; for non-special steel slabs, the target temperature is lowered according to the rolling experience of the rolling line, and the target temperature of the rolling plan issued by L3 is adjusted downward when the rolling requirements are met; according to the slab temperature determined in the system, the difference in slab width and finished product thickness is fully considered, and the target temperature is corrected;

[0010] ② Determination of the temperature at the end of each section of the slab

[0011] Use big data methods to determine the target temperature at the end of each section of the slab and establish an expert rule base;

[0012] ③ Determine the minimum time that the slab stays in the furnace

[0013] Determine the minimum time of slab in furnace according to process requirements, and optimize and adjust the minimum time of slab in furnace according to the slab charging temperature;

[0014] ④ Remaining furnace time calculation model

[0015] Through the historical slab heating performance, combined with the slab specifications and heating process parameters, the rolling interval of each steel plate is obtained, so as to obtain the remaining furnace time and remaining section time of all the existing slabs in the furnace;

[0016] ⑤ Calculation of the time the slab is in the furnace and in the section

[0017] The slab in-furnace time is calculated based on the minimum in-furnace time, the moving cycle of the walking beam, the rolling rhythm and the timed steel extraction rhythm; the slab in-section time is calculated based on the slab in-furnace time and the slab position;

[0018] ⑥ Optimization calculation of heating furnace setting temperature

[0019] The necessary furnace temperature of each section of the heating furnace is calculated based on the steel plate in the section, and the set temperature of each section of the heating furnace is calculated by weighted average according to the weight, and the final set temperature of each section is obtained after limiting;

[0020] ⑦Optimize heating furnace shutdown strategy

[0021] Based on the actual production experience of the heating furnace rest time, the furnace temperature setting value of each section of the heating furnace is determined by big data method, and an expert rule library is studied and established for the furnace temperature setting in actual production; thus, the rest strategy is adjusted according to different rest situations;

[0022] ⑧ Air excess coefficient setting model

[0023] Determine the optimal excess air coefficient for each heating furnace section based on air flow, gas flow, calorific value, and oxygen content information.

[0024] Preferably, when the target slab outlet temperature determined in the system is corrected, it does not exceed the upper and lower limit requirements.

[0025] Preferably, in determining the temperature at the end of each section of the slab, historical heating data is used to create a table from the dimensions of in-furnace time, charging temperature, and out-of-furnace temperature, and the target temperature at the end of the slab section is set. At the same time, the target temperature at the end of the slab section is reasonably adjusted after comprehensively considering factors such as steel type, width, and finished product thickness.

[0026] Preferably, the optimization calculation of the heating furnace setting temperature includes adding expert rules to meet the heating requirements of slabs with special heating requirements; making temperature rise and cooling setting corrections in advance according to the actual working conditions and process requirements of the production line; ensuring that slabs with different heating requirements are in the same furnace and the same process section under the working conditions, and the heating targets are clarified based on different needs to meet the automatic furnace firing requirements.

[0027] Beneficial effects: The method disclosed in the present invention can effectively improve the automation rate of steel burning in the heating furnace by about 20%, which has a positive significance for reducing the workload of operators and improving on-site operation efficiency. At the same time, by accurately controlling the slab heating temperature, the slab discharge temperature hit rate can be effectively improved, which has a certain effect on improving the slab heating quality. And by controlling the slab heating temperature, the fuel consumption of the heating furnace can be appropriately reduced, reducing the slab heating cost. DETAILED DESCRIPTION

[0028] In order to make the technical solution of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments.

[0029] Example

[0030] A method for intelligent steel burning in a wide and thick plate heating furnace, comprising:

[0031] Determination of target temperature of slab out of furnace

[0032] According to the target temperature requirements of the rolling plan issued by L3, special steel slabs are adjusted according to the rolling line requirements, and the priority is determined according to different requirement levels; for non-special steel slabs, the target temperature is lowered based on the rolling experience of the rolling line, and the target temperature of the rolling plan issued by L3 is adjusted downward when the rolling requirements are met; according to the slab outlet temperature determined in the system, the difference in slab width and finished product thickness is fully considered, and the target outlet temperature is corrected (not exceeding the upper and lower limits).

[0033] Determination of the temperature at the end of each section of the slab

[0034] The target temperature at the end of each section of the slab is determined by using big data methods, and an expert rule base is established. The historical heating data is mainly used to build tables from dimensions such as furnace time, furnace loading temperature, and furnace discharge temperature to set the target temperature at the end of the slab section. If necessary, the target temperature at the end of the slab section is reasonably adjusted after comprehensively considering factors such as steel type, width, and finished product thickness.

[0035] Determine the minimum slab furnace time

[0036] The minimum time that the slab stays in the furnace is determined according to the process requirements, and is optimized and adjusted according to the slab charging temperature.

[0037] Remaining furnace time calculation model

[0038] The remaining furnace time calculation model is relatively mature, and the remaining furnace time of subsequent slabs can be calculated using the current steel-out rhythm, but the premise is that the heating furnace establishes an automatic steel-out rhythm. The thick plate heating furnace is affected by factors such as variety specifications and human differences between different teams. There is a great deal of uncertainty in using the current rhythm to predict the remaining furnace time of subsequent slabs. Through the historical slab heating performance, combined with slab specifications, heating process and other parameters, the rolling interval of each steel plate is obtained, thereby obtaining the remaining furnace time and remaining segment time of all existing slabs in the furnace.

[0039] Calculation of slab in furnace and section time

[0040] The slab in-furnace time is calculated based on the minimum in-furnace time, the moving cycle of the walking beam, the rolling rhythm and the timed steel extraction rhythm; the slab in-section time is calculated based on the slab in-furnace time and the slab position;

[0041] Optimization calculation of heating furnace set temperature

[0042] The necessary furnace temperature of each section of the heating furnace is calculated based on the steel plate in the section, and the set temperature of each section of the heating furnace is calculated by weighted average according to the weight, and the final set temperature of each section is obtained after limiting. It mainly includes adding expert rules to meet the heating requirements of slabs with special heating requirements; making temperature increase and cooling settings corrections in advance according to the actual working conditions and process requirements of the production line; ensuring that slabs with different heating requirements are in the same furnace and the same process section. Under the working conditions, the heating targets are clarified based on different needs to meet the requirements of automatic furnace burning.

[0043] Optimizing heating furnace shutdown strategy

[0044] Based on the actual production experience of the heating furnace downtime, the furnace temperature setting values ​​of each section of the heating furnace are determined using big data methods, and an expert rule base is established for the actual production furnace temperature setting. The downtime strategy is adjusted according to different downtimes to achieve the goal of saving fuel and ensuring normal production at the end of the downtime.

[0045] Air excess coefficient setting model

[0046] The gas atmosphere of the heating furnace directly affects the oxidation burning and energy consumption of the steel billet. However, the combustion conditions of the heating furnace are constantly changing due to the frequent fluctuations in the calorific value of the gas during on-site production. A model is needed to determine the optimal excess air coefficient for each heating furnace section based on information such as air flow, gas flow, calorific value, and oxygen content.

[0047] According to the production slab specifications and processes, an expert library of procedures for slab heating temperatures in slab heating furnaces with different processes is established. Combined with actual on-site control requirements, upper and lower limits of temperature control in slab heating furnaces with different processes are set to ensure that the slab out-of-furnace temperature meets production requirements.

[0048]

[0049] Note: The heating codes "1, 4, 5, 9" represent slabs with different process requirements. "1" represents ordinary structural steel, which has loose requirements on heating temperature and the upper and lower limits of the furnace temperature can be controlled at ±50℃. "4" and "9" represent special steels, which have strict requirements on slab heating temperature and the upper and lower limits of the furnace temperature can be controlled at (-20, +30)℃. "5" represents mold steel, which has loose requirements on heating temperature and the upper and lower limits of the furnace temperature can be controlled at ±50℃.

[0050] In addition, a new module for writing / reading the heating furnace steel-burning model specification table is added. In the heating model system, a new model rule table data structure is added, and a specification table writing / reading function interface is developed. During model calculation, data in the expert database can be read and written in real time. A new data reading interface for the heating furnace steel-burning model specification table is added, and a new steel-burning model calculation completion event definition and event publishing logic are added.

[0051] Through the above technologies, the automation rate of the heating furnace has been effectively improved, the intelligent upgrading and transformation of the thick plate heating furnace has been promoted, the workload of personnel has been reduced, the heating quality of the slab has been improved, and the fuel consumption of slab heating has been reduced. It has full significance and value for promotion and use.

[0052] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for intelligent steel burning in a wide and thick plate heating furnace, characterized in that: include: ① Determination of target temperature of slab out of furnace According to the target temperature requirements of the rolling plan issued by L3, the special steel slabs are adjusted according to the rolling line requirements and the priorities are determined according to the different requirement levels; For non-special steel slabs, the target furnace discharge temperature is lowered based on the rolling experience of the rolling line. Under the condition that the rolling requirements are met, the target furnace discharge temperature required by the rolling plan issued by L3 is adjusted downward; according to the slab furnace discharge temperature determined in the system, the difference in slab width and finished product thickness is fully considered, and the target furnace discharge temperature is corrected; ② Determination of the temperature at the end of each section of the slab Use big data methods to determine the target temperature at the end of each section of the slab and establish an expert rule base; ③ Determine the minimum time that the slab stays in the furnace Determine the minimum time of slab in furnace according to process requirements, and optimize and adjust the minimum time of slab in furnace according to the slab charging temperature; ④ Remaining furnace time calculation model Through the historical slab heating performance, combined with the slab specifications and heating process parameters, the rolling interval of each steel plate is obtained, so as to obtain the remaining furnace time and remaining section time of all the existing slabs in the furnace; ⑤ Calculation of the time the slab is in the furnace and in the section The slab in-furnace time is calculated based on the minimum in-furnace time, the moving cycle of the walking beam, the rolling rhythm and the timed steel extraction rhythm; the slab in-section time is calculated based on the slab in-furnace time and the slab position; ⑥ Optimization calculation of heating furnace setting temperature The necessary furnace temperature of each section of the heating furnace is calculated based on the steel plate in the section, and the set temperature of each section of the heating furnace is calculated by weighted average according to the weight, and the final set temperature of each section is obtained after limiting; ⑦Optimize heating furnace shutdown strategy Based on the actual production experience of the heating furnace rest time, the furnace temperature setting value of each section of the heating furnace is determined by big data method, and an expert rule library is studied and established for the furnace temperature setting in actual production; thus, the rest strategy is adjusted according to different rest situations; ⑧ Air excess coefficient setting model Determine the optimal excess air coefficient for each heating furnace section based on air flow, gas flow, calorific value, and oxygen content information.

2. The method for intelligent steel burning in a wide and thick plate heating furnace according to claim 1 is characterized in that: When the target slab outlet temperature determined in the system is corrected, it shall not exceed the upper and lower limit requirements.

3. The method for intelligent steel burning in a wide and thick plate heating furnace according to claim 1, characterized in that: In determining the temperature at the end of each section of the slab, historical heating data is used to create a table based on the dimensions of in-furnace time, charging temperature, and out-of-furnace temperature, and the target temperature at the end of the slab section is set. At the same time, the target temperature at the end of the slab section is reasonably adjusted after comprehensively considering factors such as steel type, width, and finished product thickness.

4. The method for intelligent steel burning in a wide and thick plate heating furnace according to claim 1, characterized in that: The optimization calculation of heating furnace setting temperature includes adding expert rules to meet the heating requirements of slabs with special heating requirements; making advance corrections to the heating and cooling settings based on the actual operating conditions and process requirements of the production line; ensuring that slabs with different heating requirements are in the same furnace and the same process section under the operating conditions, and that the heating targets are clarified based on different needs to meet the requirements of automatic furnace firing.

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