阅读说明：本技术 基于尝试法的棒材水箱反向自决策控温智能计算方法 (Intelligent calculation method for reverse self-decision temperature control of bar water tank based on trial and error method ) 是由 蒲春雷 方实年 范鼎东 张明亚 周煜申 卢勇 张向军 肖元忠 于 2019-11-15 设计创作，主要内容包括：本发明基于尝试法的棒材水箱反向自决策控温智能计算方法,包括下述步骤：1)计算轧件温度分布；2)计算得出不同水箱的组合下轧件上冷床时温度内外分布,及供水系统载荷；3)以表层温度值和温度内外差值为目标函数,查找出不越界的水箱开关组合；4)尝试按预定刻度值,以供水系统最小载荷为目标函数,逐一调节每个水箱水量阀大小；5)计算调低水量阀刻度后的轧件整体的时间-温度演变曲线,与预期的cct冷却路径进行比对,满足要求则结束退出。本发明实现了快速自决策大水量快速冷却对各个水箱的控制参数,精细化按照水冷调控组织性能要求,用最快的冷却速度,在马氏体形成温度以上,确保轧件得到铁素体和珠光体,达标力学性能。(The invention relates to a trial method-based bar water tank reverse self-decision temperature control intelligent calculation method, which comprises the following steps of: 1) calculating the temperature distribution of the rolled piece; 2) calculating the temperature inside and outside distribution and the water supply system load when the rolled piece is put on a cooling bed under the combination of different water tanks; 3) using the surface temperature value and the temperature inside and outside difference value as target functions to find out the water tank switch combination which does not cross the boundary; 4) trying to regulate the size of each water tank water quantity valve one by one according to a preset scale value by taking the minimum load of a water supply system as an objective function; 5) and calculating the integral time-temperature evolution curve of the rolled piece after the water quantity valve scale is adjusted down, comparing the integral time-temperature evolution curve with the expected cct cooling path, and finishing exiting if the requirement is met. The invention realizes the control parameters of quick self-decision-making large-water-volume quick cooling on each water tank, finely adjusts and controls the structure performance requirement according to water cooling, uses the fastest cooling speed and is above the martensite forming temperature, ensures that rolled pieces obtain ferrite and pearlite and achieves the standard mechanical property.)

1. A bar water tank reverse self-decision temperature control intelligent calculation method based on a trial and error method is characterized by comprising the following steps:

1) calculating the temperature distribution of the rolled piece after the finish rolling mill according to the input steel type and specification, and the process parameters and arrangement before water penetration;

2) calculating the temperature inside and outside distribution of the water quantity valves of different water tanks when the rolled piece is put on a cooling bed under the combination of full scale or zero scale and the load of a water supply system;

3) comparing the calculated temperature distribution by taking the surface temperature value and the temperature internal and external difference value as target functions, and finding out a water tank switch combination which does not cross the boundary;

4) trying to set an opening degree scale value of +/-5% -10% randomly according to a preset scale value by taking the minimum load of a water supply system as an objective function, and adjusting the size of each water tank water valve one by one;

5) and (4) calculating the integral time-temperature evolution curve of the rolled piece after the water quantity valve scale of each water tank is adjusted, comparing the integral time-temperature evolution curve with an expected cct cooling path meeting the organization performance, finishing exiting if the requirement is met, and returning to the step 4 if the requirement is met.

2. The trial-and-error-based intelligent calculation method for reverse self-decision temperature control of a bar water tank as claimed in claim 1, wherein the method comprises the following steps: the temperature distribution of the rolled piece is calculated based on a finite difference algorithm of a Fourier heat transfer theory.

3. The trial-and-error-based intelligent calculation method for reverse self-decision temperature control of a bar water tank according to claim 1, wherein the surface temperature value, the difference between the temperature inside and outside and the minimum load of a water supply system are taken as objective functions, and the step of adjusting the size of each water tank water quantity valve one by one according to a preset scale value specifically comprises the following steps: the 1 st to the j-1 th water tanks are filled with opening degree scale values of +/-5-10% randomly, and the size of the water quantity valve of the j water tank is adjusted to be lower according to the preset scale value.

4. The trial-and-error-based intelligent calculation method for temperature control of a water tank of bars as claimed in claim 1, further comprising the step of adjusting the predetermined scale value.

Technical Field

The invention relates to an intelligent cooling control algorithm for hot rolling bar production, in particular to a bar water tank reverse self-decision temperature control intelligent calculation method based on an attempt method.

Background

The hot rolled bar generally comprises a common bar (a twisted steel bar) and a high-quality special bar (such as high-quality carbon steel, alloy structural steel, cold forging steel and the like), the total capacity of the common bar and the high-quality special bar occupies about 30% of the steel industry in China for a long time, and in the whole manufacturing process, the control of steel making, continuous casting and rolling process sections respectively form decisive influence on the product quality in the aspects of composition, segregation, organization and the like. The hot rolled bar is mainly used as a structural member, and more focuses on mechanical properties such as yield strength, tensile strength, elongation and the like, because of the limitation of welding conditions and the requirements of emergent load service conditions such as earthquake/fire, generally, the hot rolled bar pursues a refined 10-11-grade ferrite + pearlite structure as a target, and is mainly realized on the basis of a controlled rolling and cooling process and matched nozzles, water tanks, water pumps and control for a long time.

On one hand, the rolled stock has uneven temperature due to the fact that the surface of the rolled stock is relatively inner, the head and the tail of the rolled stock are relatively middle, and the corner heat exchange conditions are good; on one hand, in the bar hot rolling process, process quality fluctuation exists in the processes of continuous casting, hot feeding, heating, rough rolling and medium rolling in the previous process, so that the temperature of an intermediate rolled piece has deviation; on the one hand, the cold control equipment, especially nozzles, guide grooves and the like belong to consumption parts, and during the rapid cooling of a rolled piece and the operation of supporting the rolled piece, the formed abrasion causes uneven cooling, the three aspects jointly cause the control of the traditional cooling, the realization of high precision and stability is difficult, and the requirement on the reliability of a model and a system is high. In addition, the production line of a production enterprise is difficult to achieve complete specialization, only one steel type and specification product cannot be produced, production scheduling and conversion system processes which are closely connected in a fast-paced mode are required to be carried out along with production plans and task arrangement, the core of the change of the produced product is the change of process system parameters corresponding to the steel type and the specification, and in order to ensure high productivity and low cost, the process parameters need to be rapidly formulated according to the new change situation on the production line, and a model and an algorithm for cooling are controlled to become a key.

At present, the establishment of the cooling control parameters of the hot rolled bars on site is mainly based on an empirical method, and after a large number of cooling control process values of steel types and specifications are accumulated, after actual steel running on site is debugged for about 3-5 times, the applicable value is obtained and is used for a period of time, when the final detection value is unqualified in the cold bed temperature and tissue performance spot check, the parameters are replaced, the method not only wastes time and labor, and has no theoretical guidance, is difficult to solidify, can not give full play to the production line capacity, and is based on the Fourier heat transfer principle, the temperature change is predicted by forming rolled piece temperature calculation software through a difference method and combining the formulas of water pressure, water flow and the like on heat exchange coefficients obtained through experience or experiments, compared with a pure experience method, the method is improved, however, the heat exchange coefficient value is not stable with the change of the working condition, needs to be updated and is not always reflected in software. In addition, in practical application, what is needed most is that under the given new steel type and specification, for the specific production line water tank arrangement situation, based on the upper cooling bed temperature value (or required value), whether each specific water tank is opened or closed and the opening threshold value amount under the opening are quickly and directionally given, rather than just uniformly regulating and controlling each water tank, the cooling temperature value is reached, the structure principle of the deformed steel bar and the actual cooling control requirement are regulated and controlled according to the metallurgy of materials, the deformed steel bar is quickly cooled with large water volume, under the condition that the final cooling temperature and the final cooling temperature are not formed into martensite, the fastest cooling speed is used to drive the least water tanks, and the requirements exceed the capability of the current bar cooling control model and system.

Disclosure of Invention

In order to overcome the defects, the invention aims to provide a bar water tank reverse self-decision temperature control intelligent calculation method based on a trial and error method, which is more advanced, reasonable, simple to operate and less in investment, so as to complete adjustment of process parameters of each water tank based on-line steel types and specification requirements.

In order to achieve the aim, the intelligent calculation method for reverse self-decision temperature control of the bar water tank based on the trial and error method comprises the following steps:

1) calculating the temperature distribution of the rolled piece after the finish rolling mill according to the input steel type and specification, and the process parameters and arrangement before water penetration;

2) calculating the temperature inside and outside distribution of the water quantity valves of different water tanks when the rolled piece is put on a cooling bed under the combination of full scale or zero scale, and the load of a water supply system (comprising a main pipe and a branch pipe);

3) comparing the calculated temperature distribution by taking the surface temperature value and the temperature internal and external difference value as target functions, and finding out a water tank switch combination which does not cross the boundary;

4) trying to set an opening degree scale value of +/-5% -10% randomly according to a preset scale value by taking the minimum load of a water supply system as an objective function, and adjusting the size of each water tank water valve one by one;

5) and (4) calculating the integral time-temperature evolution curve of the rolled piece after the water quantity valve scale of each water tank is adjusted, comparing the integral time-temperature evolution curve with an expected cct cooling path meeting the organization performance, finishing exiting if the requirement is met, and returning to the step 4 if the requirement is met.

Further, the method comprises the following steps: the temperature distribution of the rolled piece is calculated based on a finite difference algorithm of a Fourier heat transfer theory.

Further, the step of adjusting the size of each water tank water quantity valve one by one according to the preset scale value specifically comprises the following steps: the method comprises the following steps of taking a surface temperature value, a temperature internal and external difference value and a water supply system minimum load as objective functions, and adjusting the size of each water tank water volume valve one by one according to a preset scale value: the 1 st to the j-1 th water tanks are filled with opening degree scale values of +/-5-10% randomly, and the size of the water quantity valve of the j water tank is adjusted to be lower according to the preset scale value.

Further, the method also comprises the step of reducing the preset scale value.

The invention relates to a bar water tank inverse self-decision temperature control intelligent calculation method based on an trial method, which is based on a Fourier heat transfer two-dimensional differential evolution equation, firstly tries the upper cooling bed temperature condition after a rolled piece is cooled under different conditions of one or more water tanks being fully opened for preset (or detected) bar surface temperature and section temperature difference, then judges whether a given preset requirement is out of range or not according to the maximum cooling and full air cooling results, finds out the total number and specific objects of open water tanks under the condition of not out of range, then gradually optimizes the opening degree parameter of an adjustable specific water tank in a range according to the cooling control process requirement after the number of the open water tanks is determined, finds out the optimal value, compares the output rolled piece cooling curve with the required cooling path meeting the product organization performance, and outputs the result when the requirement is met. The control parameters of the large-water-volume quick cooling on each water tank are quickly and automatically decided, the requirements of regulating and controlling the structure performance according to water cooling are refined, the minimum water tanks are opened, the highest cooling speed is used, the temperature above the martensite forming temperature is ensured, and the rolled piece is ensured to obtain ferrite and pearlite and reach the mechanical performance.

Drawings

FIG. 1 is a block diagram of a bar water tank reverse self-decision temperature control intelligent calculation method based on a trial and error method

Detailed Description

In a typical hot rolled bar rolling line, there are generally 18 stands, a roughing mill train 6, a medium mill train 6, and a finishing mill train 6. The rolling temperature is generally 950-1200 ℃, the temperature of the rolled piece after being taken out of the final rolling mill is about 900-1100 ℃ after 18-pass rolling, on one hand, the temperature of the high-temperature rolled piece is required to be rapidly reduced to room temperature for subsequent finishing;

on one hand, according to the principle of low-carbon steel material metallurgy continuous cooling transformation, the cooling speed caused by a reasonable cooling path can ensure that high-temperature austenite of a high-temperature rolled piece forms fine ferrite, pearlite refinement is promoted, and good structure performance is obtained;

on the one hand, the cooling strength at high cooling rates is not so great that an unfavourable martensitic structure is formed. Consequently, after the finishing mill group, can arrange the multiunit water tank, through discharge, the water pressure control to every water tank, realize controlling the rolled piece cooling strength who walks, water tank quantity is generally between 1 ~ 4 group, and between two adjacent water tanks simultaneously, the natural air cooling distance that can also place certain length distance forms the heart to the recovery on surface.

In the traditional temperature regulation and control of the rolled piece of the bar, the final surface temperature of the bar is usually only taken as a target, the requirement of cooling path control on a microstructure required by the bar is neglected essentially, and the developed model and system only realize temperature calculation under specific process parameters by using a Fourier heat conduction differential equation and do not have a model algorithm for back-calculating the optimal parameters of a water tank.

The invention provides a bar water tank inverse self-decision temperature control intelligent calculation method based on a trial method. And then according to the on-site process arrangement of the water passing water tanks, calculating temperature values and distribution when rolled pieces are put on a cooling bed under different water tank combinations (only the switch is considered), comparing the temperature values and the distribution with the steel temperature requirement (detection value) and the temperature distribution requirement (generally less than 50 ℃) on the cooling bed, and directly exiting the program calculation if the temperature values and the distribution exceed the threshold.

The method comprises the following steps of trying to obtain an optimal water tank switch combination without crossing the boundary, and adjusting the size of each water tank water quantity valve one by one according to a preset scale value by taking a surface temperature value, a temperature internal and external difference value and a water supply system minimum load as an objective function: and (3) placing a random +/-5% -10% opening degree scale value into the 1 st to the j-1 th water tanks, adjusting the sequence of a water quantity valve by the j-th water tank, optimizing a cooling path by a path with a large interval scale and a small interval scale, obtaining the time-temperature evolution curve of the whole rolled piece, comparing the time-temperature evolution curve with the expected cct cooling path meeting the organizational performance, finishing the exit procedure if the requirement is met, otherwise, combining a group of new water tanks, and trying again until the error is met.

Based on the optimization of the interval scales, the range of the optimal parameters can be quickly reduced, the searching time is further shortened, and the optimal result can be obtained more quickly. By the treatment of the invention, the cooling path requirement based on the stable controlled cooling process can be achieved under the lowest investment, and the product organization performance of the rolled piece is improved.

In specific operation, when the preset scale value of the water quantity adjusting valve is larger, the optimizing speed is higher, for example, when the scale is 25, but the precision is correspondingly lower. Therefore, when the preset scale value of the water quantity valve is adjusted to be smaller, the optimizing speed is relatively slower, for example, 5 scales. But the accuracy will be correspondingly higher. Therefore, the preset scale value can be adjusted according to actual needs, and the precision and the speed can be guaranteed. The predetermined scale value may range from 1 to 30.

In summary, the novel bar water tank reverse self-decision temperature control intelligent calculation method based on the trial method provided by the invention is based on the Fourier difference algorithm to calculate the temperature, and based on the steel type, specification, process parameters and arrangement before final rolling and the arrangement of water tanks after rolling, aiming at the goal of meeting the cct curve cooling curve of the product structure performance, a water tank combination switch is added in the calculation and the opening degree is tried to be calculated from the last water tank in a reverse mode to form a calculation cooling curve, and through comparison, the intelligent calculation of reverse sub-decision is realized, so that the requirements of meeting the cooling requirement of a rolled piece, controlling the organization and meeting the mechanical performance can be met as far as possible under the condition that the existing rolling line is reconstructed as little as possible.