CN104498654A - Blast furnace temperature change trend determination method and device - Google Patents

Abstract

The invention discloses a method and device for determining the temperature change trend of a blast furnace. The flame temperature and the relative brightness of the flame in the tuyere swirl area; and when the flame temperature is greater than the first flame temperature threshold and the relative brightness of the flame is greater than the first flame relative brightness threshold, the first furnace temperature index is determined to be the first preset furnace temperature index; When the flame temperature is less than the second flame temperature threshold and the relative brightness of the flame is less than the second flame relative brightness threshold, determine that the first furnace temperature index is the second preset furnace temperature index; otherwise, determine that the first furnace temperature index is zero; and Based on the first furnace temperature index, the variation trend of the blast furnace temperature is determined. By adopting the solution provided by the embodiment of the present invention, the temperature variation trend of the blast furnace can be determined more accurately.

Description

A method and device for determining the trend of blast furnace temperature variation

technical field

The invention relates to the technical field of blast furnace smelting, in particular to a method and device for determining the variation trend of blast furnace temperature.

Background technique

Blast furnace ironmaking is an important link in the iron and steel industry. Its process is characterized by nonlinearity, strong coupling, large time delay, and contains hundreds of physical and chemical reactions, making it difficult to use a certain method to monitor the internal state of the blast furnace.

In order to ensure the stable and smooth operation of the blast furnace, it is beneficial to reduce costs, increase production, improve economic benefits, and meet the requirements of green energy conservation. The blast furnace temperature is the embodiment of the blast furnace's stable operation, so the judgment of the blast furnace temperature is particularly critical.

In the actual industrial process, the internal thermal state of the blast furnace is judged manually based on human experience, and there is a lack of unified criteria for judging. Moreover, the reference information is complex and diverse, and the changes in various furnace temperature symptoms of the blast furnace have different effects on the furnace temperature, which brings great difficulties to manual judgment.

Contents of the invention

The embodiments of the present invention provide a method and device for determining the variation trend of the blast furnace temperature to solve the problem in the prior art that the variation trend of the blast furnace temperature cannot be accurately determined.

An embodiment of the present invention provides a method for determining the temperature variation trend of a blast furnace, including:

Obtain the image obtained by taking pictures of the tuyere swirl area of the blast furnace;

Based on the pixel value of the pixel point in the image, the temperature of the flame and the relative brightness of the flame in the tuyere swirl area in the image are determined by using a radiation thermometry method;

When the flame temperature is greater than the first flame temperature threshold and the flame relative brightness is greater than the first flame relative brightness threshold, the first furnace temperature index is determined to be the first preset furnace temperature index, and the first preset furnace temperature The index indicates that the temperature change trend of the blast furnace is temperature increase;

When the flame temperature is less than the second flame temperature threshold and the flame relative brightness is less than the second flame relative brightness threshold, it is determined that the first furnace temperature index is the second preset furnace temperature index, wherein the first The flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature decrease;

Otherwise, it is determined that the first furnace temperature index is zero, indicating that the furnace temperature change trend of the blast furnace is to keep the temperature within a reasonable range;

Based on the first furnace temperature index, the variation trend of the furnace temperature of the blast furnace is determined.

Further, before determining the change trend of the blast furnace temperature based on the first furnace temperature index, it also includes:

determining at least one of the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index;

Wherein, adopt the following steps to determine the second furnace temperature index:

Determine the edge temperature index and central temperature index of the blast furnace throat, wherein the edge temperature index represents the situation of the edge temperature of the blast furnace throat relative to the average temperature of the blast furnace throat, and the central temperature index represents the relative temperature of the center temperature of the blast furnace throat The condition of the average temperature of the furnace throat;

When the edge temperature index is greater than the first edge temperature index threshold and the center temperature index is greater than the first center temperature index threshold, determine that the second furnace temperature index is the first preset furnace temperature index;

When the edge temperature index is less than the second edge temperature index threshold and the center temperature index is less than the second center temperature index threshold, the second furnace temperature index is determined to be the second preset furnace temperature index, wherein, the first edge temperature index threshold is greater than the second edge temperature index threshold, and the first core temperature index threshold is greater than the second core temperature index threshold;

Otherwise, determine that the second furnace temperature index is zero;

Adopt the following steps to determine the third furnace temperature index:

Determining the blanking acceleration corresponding to each of the multiple probes, and the acceleration standard deviation of the blanking acceleration corresponding to each of the multiple probes;

When for each probe, the feeding acceleration corresponding to the probe is less than the negative value of the sum of the first speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the first preset furnace temperature index;

When for each probe, the feeding acceleration corresponding to the probe is greater than the sum of the second speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the second preset furnace temperature index ;

Otherwise, determine that the third furnace temperature index is zero;

The following steps are adopted to determine the fourth furnace temperature index:

Obtain the temperature of the blast furnace wall at multiple different heights in the blast furnace wall, and the temperature of the outer surface of the stave at the multiple different heights;

Based on the temperature of the blast furnace wall at the multiple different heights and the temperature of the outer surface of the stave, and according to the two-dimensional heat transfer mechanism model of the cross section of the blast furnace wall, determine the inner surface temperature of the blast furnace at the multiple different heights;

When for each height, the blast furnace inner surface temperature at the height is greater than the first blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the first preset furnace temperature index;

When for each height, the blast furnace inner surface temperature at that height is less than the second blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the second preset furnace temperature index, wherein, for each height, the temperature threshold of the first blast furnace inner surface corresponding to the height is greater than the second blast furnace inner surface temperature threshold corresponding to the height;

Otherwise, determine that the fourth temperature index is zero;

Use the following steps to determine the fifth furnace temperature index:

Obtain the current values of various input parameters required to determine the silicon content of the blast furnace hot metal based on the silicon content prediction model of the molten iron;

Determining the silicon content of the blast furnace molten iron according to the obtained current values of the various input parameters and according to the prediction model for the silicon content of the molten iron;

When the silicon content of the blast furnace hot metal is greater than the first preset blast furnace silicon threshold, the fifth furnace temperature index is determined as the first preset furnace temperature index;

When the silicon content of the blast furnace molten iron is less than the second preset blast furnace silicon threshold, the fifth furnace temperature index is determined to be the second preset furnace temperature index, wherein the first preset blast furnace silicon threshold is greater than The second preset blast furnace molten iron silicon threshold;

Otherwise, determine that the fifth furnace temperature index is zero;

Based on the first furnace temperature index, determining the variation trend of the blast furnace temperature includes:

Determine the blast furnace based on the first furnace temperature index and at least one of the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index Variation trend of furnace temperature.

Further, the edge temperature index is the sum of the edge temperatures obtained by cross-measurement of the blast furnace throat, divided by four times the average top temperature of the throat temperature obtained by the cross-measurement;

The central temperature index is the sum of the central temperature obtained by performing the cross temperature measurement and the temperature of the four points close to the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement; or, The center temperature index is the sum of the center temperature obtained by performing the cross temperature measurement and the temperature of the four points near the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement and the preset The product of constants, the preset constant is greater than 1.

Further, the following steps are adopted to determine the prediction model of the silicon content in molten iron:

In the preset time period, according to the preset time interval, various input parameter values of the molten iron silicon content prediction model are collected, and the multiple values of each input parameter collected are normalized respectively, and the normalized Various input parameter values of ;

During the preset time period, at the moment when the blast furnace molten iron is produced, the silicon content of the molten iron in the blast furnace produced at this time is collected;

Based on the silicon content of molten iron collected multiple times, curve fitting is performed according to the time axis to obtain a silicon content curve of molten iron within the preset time period;

Determining the silicon content of molten iron corresponding to each sampling moment according to the preset time interval in the silicon content curve of the molten iron;

Based on the normalized various input parameter values and the determined silicon content of molten iron corresponding to each sampling time interval according to the preset time interval, a prediction model of silicon content in molten iron is established according to a support vector regression method.

Further, based on the first furnace temperature index and at least one of the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index , to determine the variation trend of blast furnace temperature, including:

Based on the first furnace temperature index, and at least one of the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index, and each The weight corresponding to the furnace temperature index is weighted and summed to obtain the comprehensive furnace temperature index;

When the comprehensive furnace temperature index is greater than the first furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is temperature rise, and the first furnace temperature index threshold is greater than zero and less than the first preset furnace temperature index;

When the comprehensive furnace temperature index is less than the second furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is a temperature decrease, and the second furnace temperature index threshold is greater than the second preset furnace temperature index and less than zero, so The second preset furnace temperature index is negative for the first preset furnace temperature index;

Otherwise, determine the variation trend of blast furnace temperature to keep the temperature within a reasonable range.

The embodiment of the present invention also provides a blast furnace temperature change trend determination device, including:

an image acquisition unit, configured to acquire an image obtained by taking pictures of the blast furnace tuyere swirl;

The temperature and brightness determination unit is used to determine the flame temperature and the relative brightness of the flame in the tuyere swirl area in the image based on the pixel values of the pixel points in the image by means of radiation thermometry;

The first furnace temperature index determining unit is configured to determine the first furnace temperature index as the first preset furnace temperature when the flame temperature is greater than the first flame temperature threshold and the relative brightness of the flame is greater than the first flame relative brightness threshold index, the first preset furnace temperature index indicates that the temperature change trend of the blast furnace is a temperature increase; and

When the flame temperature is less than the second flame temperature threshold and the flame relative brightness is less than the second flame relative brightness threshold, it is determined that the first furnace temperature index is the second preset furnace temperature index, wherein the first The flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the furnace temperature of the blast furnace tends to decrease in temperature; and

Otherwise, it is determined that the first furnace temperature index is zero, indicating that the furnace temperature change trend of the blast furnace is to keep the temperature within a reasonable range;

The change trend determination unit is configured to determine the change trend of the blast furnace temperature based on the first furnace temperature index.

The beneficial effects of the present invention include:

In the method provided by the embodiment of the present invention, during the blast furnace smelting process, the tuyere swirl area of the blast furnace can be photographed, and the obtained image can be obtained, and then based on the pixel values of the pixels in the image, the radiation temperature measurement method can be used to determine the temperature in the image. The flame temperature and flame relative brightness in the tuyere swirl area, when the flame temperature is greater than the first flame temperature threshold, and the flame relative brightness is greater than the first flame relative brightness threshold, determine the first furnace temperature index as the first preset furnace temperature index, the first A preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature rise. When the flame temperature is less than the second flame temperature threshold and the relative brightness of the flame is smaller than the second flame relative brightness threshold, the first furnace temperature index is determined to be the second predetermined value. The furnace temperature index is set, and the second preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature reduction; otherwise, the first furnace temperature index is determined to be zero, indicating that the temperature change trend of the blast furnace is to keep the temperature within a reasonable range, and then A furnace temperature index to determine the change trend of the blast furnace temperature, thereby realizing the accurate determination of the change trend of the blast furnace temperature.

Additional features and advantages of the application will be set forth in the description which follows, and, in part, will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Description of drawings

The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the description, and are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the attached picture:

Fig. 1 is a flow chart of the method for determining the variation trend of blast furnace temperature provided by an embodiment of the present invention;

Fig. 2 is a flow chart of determining the second temperature index representing the variation trend of the blast furnace temperature based on the temperature of the blast furnace throat in an embodiment of the present invention;

Fig. 3 is a flow chart of determining the third temperature index representing the variation trend of blast furnace temperature based on the blanking speed of blast furnace raw materials in an embodiment of the present invention;

Fig. 4 is a flow chart of determining the fourth temperature index representing the variation trend of the blast furnace temperature based on the temperature of the inner surface of the blast furnace in an embodiment of the present invention;

Fig. 5 is a flow chart of determining the fifth temperature index representing the variation trend of blast furnace temperature based on the silicon content of blast furnace molten iron in an embodiment of the present invention;

Fig. 6 is the flow chart of the method for determining the silicon content model of molten iron in the embodiment of the present invention;

Fig. 7 is a flowchart of determining the change trend of blast furnace temperature based on five furnace temperature indices in an embodiment of the present invention;

Fig. 8 is a schematic structural diagram of a blast furnace temperature variation trend determination device provided by an embodiment of the present invention.

Detailed ways

In order to provide an accurate implementation plan for determining the variation trend of the blast furnace temperature, the embodiment of the present invention provides a method and device for determining the variation trend of the blast furnace temperature. The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that, The preferred embodiments described here are only used to illustrate and explain the present invention, not to limit the present invention. And in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

The embodiment of the present invention provides a method for determining the variation trend of blast furnace temperature, as shown in FIG. 1 , including:

Step 11. Obtain an image obtained by taking pictures of the tuyere swirl area of the blast furnace.

Step 12. Based on the pixel values of the pixel points in the image, the temperature of the flame and the relative brightness of the flame in the tuyere swirl area in the image are determined by means of radiation temperature measurement.

Step 13. When the flame temperature is greater than the first flame temperature threshold and the relative brightness of the flame is greater than the first flame relative brightness threshold, determine that the first furnace temperature index is the first preset furnace temperature index, and the first preset furnace temperature index indicates that the blast furnace The trend of furnace temperature is temperature rise.

Step 14. When the flame temperature is less than the second flame temperature threshold and the relative flame brightness is less than the second flame relative brightness threshold, determine that the first furnace temperature index is the second preset furnace temperature index, wherein the first flame temperature threshold is greater than the second flame temperature threshold Two flame temperature thresholds, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature decrease.

Step 15. Otherwise, it is determined that the first furnace temperature index is zero, which means that the variation trend of the blast furnace temperature is to keep the temperature within a reasonable range.

Step 16. Based on the first furnace temperature index, determine the variation trend of the blast furnace temperature.

Among them, the flame temperature threshold and the flame relative brightness threshold can be flexibly set according to the needs with reference to various actual situations in the actual application, for example, various attributes of the blast furnace itself, various attributes of the blast furnace raw materials, etc.

In the method for determining the temperature change trend of the blast furnace shown in Figure 1 above, a detector can be installed at the end of the blast furnace tuyere peep hole, and the camera of the detector can be used to take pictures of the blast furnace tuyere roundabout area, thereby obtaining an image of the blast furnace tuyere roundabout area .

Moreover, when determining the flame temperature and the relative brightness of the flame in the tuyere swirl area in the image, the three-primary color radiation temperature measurement method can be used to determine the flame temperature and the relative brightness of the flame by extracting the gray value of the image. The specific algorithm can refer to the existing Relevant technologies of image processing will not be described in detail here.

Using the method shown in Figure 1 above, based on the images taken of the tuyere swirl area of the blast furnace, the flame temperature and the relative brightness of the flame in the tuyere swirl area of the blast furnace are determined, so as to realize the determination of the temperature change trend of the blast furnace. Since there are standard judgment criteria, Therefore, the variation trend of blast furnace temperature can be accurately determined.

In the embodiment of the present invention, in order to determine the change trend of the blast furnace temperature more accurately, other characteristics in the blast furnace smelting process can also be collected, and combined with the flame temperature and the relative brightness of the flame in the tuyere swirl area of the blast furnace, to determine the temperature of the blast furnace. Furnace temperature change trend, for example, can also refer to the temperature of the blast furnace throat, the feeding speed of the blast furnace raw materials, the temperature of the inner surface of the blast furnace, and the silicon content of the blast furnace molten iron. The scheme for determining the variation trend of blast furnace temperature is described in detail.

Fig. 2 is a flow chart of determining the second temperature index representing the variation trend of the blast furnace temperature based on the temperature of the blast furnace throat, which may specifically include the following steps:

Step 21, based on the temperature of the blast furnace throat, determine the flow chart of the second temperature index representing the variation trend of the blast furnace temperature, and obtain the temperatures of each throat of the blast furnace obtained by cross-measuring the blast furnace throat.

For the cross temperature measurement of the blast furnace throat, you can use a temperature measuring gun to measure the temperature at the center, edge, and preset positions between the center and the edge of the blast furnace throat respectively to obtain four edge temperatures and one center temperature. temperature, and the temperature at each preset position between the center and the edge.

Step 22. Determine the average value of the temperature of each furnace throat obtained by cross temperature measurement as the average value of the top temperature.

Step 23, determine the edge temperature index of the blast furnace throat, and the edge temperature index represents the situation of the edge temperature of the blast furnace throat relative to the average temperature of the blast furnace throat.

The edge temperature index can be the sum of the edge temperatures obtained by cross-measuring the blast furnace throat, divided by 4 times the average top temperature of the throat temperature obtained by cross-measuring, and the following formula can be used specifically:

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; a</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}}{\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ;</span>$

Among them, F _b is the edge temperature index, T _a , T _b , T _c and T _d are the four edge temperatures obtained by cross temperature measurement, and T is the average top temperature.

Step 24. Determine the central temperature index of the blast furnace throat, which represents the situation of the central temperature of the blast furnace throat relative to the average temperature of the blast furnace throat.

The central temperature index can be the sum of the central temperature obtained by cross temperature measurement and the temperature of four points close to the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by cross temperature measurement. The following formula can be used specifically:

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; z</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; 5</span>}\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; ;</span>$

Among them, F _z is the center temperature index, T _e , T _f , T _g and _Th are the temperatures of the four points near the center obtained by cross temperature measurement, T _i is the center temperature obtained by cross temperature measurement, and T is the average top temperature .

Considering that the center temperature is relatively high, when determining the center temperature index, it can also be the sum of the center temperature obtained by cross temperature measurement and the temperature of the four points near the center, divided by the top of the furnace throat temperature obtained by cross temperature measurement. The product of 5 times the average temperature and a preset constant, and the preset constant is greater than 1. For example, the preset constant is 2.5. The following formula can be used specifically:

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; z</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; g</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; 2.5</span>}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; 5</span>}\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; .</span>$

Step 25. Determine whether the edge temperature index is greater than the first edge temperature index threshold and whether the core temperature index is greater than the first core temperature index threshold. If both are greater, go to step 26; otherwise, go to step 27.

Step 26. Determine the second furnace temperature index as the first preset furnace temperature index.

Step 27. Determine whether the edge temperature index is less than the second edge temperature index threshold and whether the core temperature index is less than the second core temperature index threshold. If both are less than, go to step 28; otherwise, go to step 29.

Wherein, the first edge temperature index threshold is greater than the second edge temperature index threshold, the first core temperature index threshold is greater than the second core temperature index threshold, the values of each threshold can refer to various actual situations in actual application, and It can be set flexibly according to needs, and the distance will not be described here.

Step 28. Determine the second furnace temperature index as the second preset furnace temperature index.

Step 29. Determine that the second furnace temperature index is zero.

Fig. 3 is a flow chart of determining the third temperature index representing the variation trend of the blast furnace temperature based on the blanking speed of the blast furnace raw material, which may specifically include the following steps:

Step 31. During the blast furnace smelting process, raw materials need to be added to the blast furnace. At this time, the feeding speed of the raw materials can be detected by a probe. For example, the feeding speed can be determined by the following formula:

$\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&Delta;l</span>}}{\mathrm{<span\; class="notranslate">\; \&Delta;T</span>}}<span\; class="notranslate">\; ;</span>$

Among them, v is the feeding speed, ΔT is the preset detection cycle, and Δl is the depth of the dipping probe in the current cycle.

Step 32, adopt the following formula to determine the blanking acceleration:

$\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&Delta;T</span>}}<span\; class="notranslate">\; ;</span>$

Wherein, a is the feeding acceleration, v(i+1) is the feeding speed detected in the current preset detection cycle, and v(i) is the feeding speed detected in the previous preset detection cycle.

Step 33, using the following formula to determine the acceleration standard deviation of the blanking acceleration corresponding to each of the plurality of probes:

a _max = max(a _i );

a _min =min(a _i );

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; aver</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; min</span>}}}{\mathrm{<span\; class="notranslate">\; \&Delta;T</span>}}<span\; class="notranslate">\; ;</span>$

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; std</span>}}<span\; class="notranslate">\; =</span>\frac{\sqrt{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; aver</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; ;</span>$

Among them, a _i is the blanking acceleration corresponding to the i-th probe in the n probes, a _max is the maximum value of the blanking accelerations corresponding to the n probes, and a _min is the bottom acceleration corresponding to the n probes. The minimum value of material acceleration, a _std is the acceleration standard deviation of the corresponding blanking acceleration of n probes.

Step 34. For each of the plurality of probes, determine whether the blanking acceleration corresponding to the probe is less than the negative value of the sum of the first speed threshold and the acceleration standard deviation. If it is less than for each probe, enter Step 35, otherwise, go to step 36.

That is, it is determined whether a _i <-(b ₁ +a _std ), where b ₁ is the first speed threshold.

Step 35. Determine the third furnace temperature index as the first preset furnace temperature index.

Step 36. For each of the plurality of probes, determine whether the blanking acceleration corresponding to the probe is greater than the sum of the second speed threshold and the acceleration standard deviation. If it is greater than the second speed threshold for each probe, go to step 37. Otherwise, go to step 38.

That is, it is determined whether a _i >(b ₂ +a _std ), where b ₂ is the second speed threshold.

Among them, the values of the first speed threshold and the second speed threshold can be flexibly set according to the needs with reference to various actual situations in actual application. For example, the first speed threshold can be set to 0.007, and the second speed threshold The threshold can take a value of 0.002.

Step 37. Determine the third furnace temperature index as the second preset furnace temperature index.

Step 38. Determine that the third furnace temperature index is zero.

Fig. 4 is a flow chart of determining the fourth temperature index representing the change trend of the blast furnace temperature based on the temperature of the inner surface of the blast furnace, which may specifically include the following steps:

Step 41. Acquire blast furnace wall temperatures at multiple different heights in the blast furnace wall.

Specifically, temperature-measuring thermocouples can be arranged at multiple different heights in the refractory bricks of the blast furnace wall to detect the temperature of the blast furnace wall at multiple different heights in the blast furnace wall.

Step 42, obtaining the temperature of the outer surface of the cooling wall at different heights.

The temperature of the outer surface of the cooling wall can be detected by arranging a temperature sensor at the inlet and outlet of the cooling wall.

Step 43. Based on the multiple blast furnace wall temperatures and cooling wall outer surface temperatures at different heights, and according to the two-dimensional heat transfer mechanism model of the blast furnace wall cross-section, determine the multiple blast furnace inner surface temperatures at different heights.

For example, it can be determined based on the following formula:

$\frac{<span\; class="notranslate">\; \&PartialD;</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}\frac{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; r</span>}}\frac{<span\; class="notranslate">\; \&PartialD;</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&lambda;r</span>}\frac{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; r</span>}}\frac{<span\; class="notranslate">\; \&PartialD;</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}{\mathrm{<span\; class="notranslate">\; r</span>}}\frac{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; q</span>}}_{\mathrm{<span\; class="notranslate">\; v</span>}}}{\mathrm{<span\; class="notranslate">\; \&rho;c</span>}}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; T</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&PartialD;</span>\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; ;</span>$

Among them, h is the axial height of the blast furnace, _r is the radius, θ is the circumferential radian, λ is the thermal conductivity, qv is the internal heat source, ρ is the density, c is the specific heat capacity, T is the temperature, and τ is the time.

Step 44. For each of the multiple heights, determine whether the blast furnace inner surface temperature at the height is greater than the first blast furnace inner surface temperature threshold corresponding to the height. If it is greater than the first blast furnace inner surface temperature threshold for each height, go to step 45, otherwise , go to step 46.

Step 45. Determine the fourth furnace temperature index as the first preset furnace temperature index.

Step 46. For each of the multiple heights, determine whether the blast furnace inner surface temperature at the height is less than the second blast furnace inner surface temperature threshold corresponding to the height. If it is less than the second blast furnace inner surface temperature threshold for each height, go to step 47, otherwise , go to step 48.

Wherein, for each height, the first blast furnace inner surface temperature threshold corresponding to the height is greater than the second blast furnace inner surface temperature threshold corresponding to the height, and the values of each threshold can refer to various actual situations in actual application, And it can be set flexibly according to needs, and no example will be described here.

Step 47. Determine the fourth furnace temperature index as the second preset furnace temperature index.

Step 48. Determine that the fourth temperature index is zero.

Fig. 5 is a flow chart for determining the fifth temperature index representing the variation trend of the blast furnace temperature based on the silicon content of the blast furnace molten iron, which may specifically include the following steps:

Step 51. Obtain the current values of various input parameters required to determine the silicon content of the blast furnace molten iron based on the prediction model of the silicon content of the molten iron.

For example, various input parameters of the molten iron silicon content prediction model may include: wind pressure, pressure difference, air volume, air permeability index, top pressure, top temperature, wind temperature, Si content of the previous hot metal, etc.

Step 52 , based on the obtained current values of various input parameters, and according to the silicon content prediction model of the molten iron, determine the silicon content of the blast furnace molten iron.

Step 53 : Determine whether the silicon content of the blast furnace hot metal is greater than the first preset blast furnace silicon threshold, and if so, go to step 54 ; otherwise, go to step 55 .

Step 54. Determine the fifth furnace temperature index as the first preset furnace temperature index.

Step 55 : Determine whether the silicon content of the blast furnace hot metal is less than a second preset threshold value of silicon in the blast furnace hot metal, and if so, go to step 56 ; otherwise, go to step 57 .

Among them, the first preset blast furnace molten iron silicon threshold value is greater than the second preset blast furnace molten iron silicon threshold value, and the values of each threshold value can refer to various actual situations in actual application, and can be flexibly set according to needs, and will not be discussed here. Describe with an example.

Step 56. Determine the fifth furnace temperature index as the second preset furnace temperature index.

Step 57. Determine that the fifth furnace temperature index is zero.

In the flow process shown in Figure 5 above, the silicon content prediction model of molten iron can adopt various silicon content prediction models of molten iron in the prior art. In the embodiment of the present invention, a new method for determining the silicon content model of molten iron is proposed, as shown in Fig. 6, specifically including the following processing steps:

Step 61, within the preset time period, according to the preset time interval, collect various input parameter values of the molten iron silicon content prediction model to be established, wherein the various input parameters can be flexibly set according to actual needs, for example, can be All or any combination of the above parameters will not be described here as examples.

Step 62. Since the magnitudes of various parameter values may vary greatly, in order to improve the rationality of model establishment, the multiple values of each input parameter collected can be normalized separately to obtain normalized After various input parameter values, the following formula can be used to normalize multiple values of each input parameter:

${\stackrel{<span\; class="notranslate">\; -</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; min</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; max</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; min</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ;</span>$

Among them, x _i (k) is the i-th value among the n values of the k-th input parameter in the collected m kinds of input parameters, is the normalized value corresponding to the i-th value among the n values of the k-th input parameter among the collected m kinds of input parameters.

Step 63, within the preset time period, at the moment when the blast furnace molten iron is produced, collect the silicon content of the molten iron in the blast furnace produced at this time.

Step 64: Based on the silicon content of the molten iron collected multiple times within the preset time period, perform curve fitting according to the time axis to obtain a silicon content curve of the molten iron within the preset time period.

Step 65 , determining the silicon content of the molten iron corresponding to each sampling time according to the preset time interval in the silicon content curve of the molten iron.

Step 66 : Based on the above-mentioned normalized various input parameter values and the determined silicon content of molten iron corresponding to each sampling moment according to the preset time interval, a prediction model of silicon content in molten iron is established according to the support vector regression method.

Specifically, a prediction model for silicon content in molten iron can be established based on the following formula:

$\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{{\mathrm{<span\; class="notranslate">\; c</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; d</span>}<span\; class="notranslate">\; ;</span>$

Among them, x is the sample to be predicted, _xi is the training sample, _ci , _ci ^* is the Lagrangian multiplier, d is the deviation, k( _xi ,x) can be selected as the RBF kernel function, the details can be as follows :

$\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>\frac{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}{{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; )</span>$

In the embodiment of the present invention, when at least one of the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index is determined through the processes shown in the above-mentioned Figures 2-5, correspondingly, Based on the first furnace temperature index, determine the change trend of blast furnace temperature, which can be expressed as:

Based on the first furnace temperature index and at least one of the determined second furnace temperature index, third furnace temperature index, fourth furnace temperature index and fifth furnace temperature index, the variation trend of the blast furnace temperature is determined.

For example, among the various furnace temperature indices involved in determining the variation trend of the blast furnace temperature, the number of the first preset furnace temperature index and the number of the second preset furnace temperature index can be determined separately, if the former number is greater than the latter number , then it is determined that the temperature change trend of the blast furnace is temperature increase. If the former number is less than the latter number, then the blast furnace temperature change trend is determined as temperature decrease. If they are equal, the blast furnace temperature change trend is to keep the temperature within a reasonable range.

For another example, it is also possible to set priorities for each furnace temperature index involved in determining the variation trend of the blast furnace temperature, and judge according to the order of priority from high to low. If the blast furnace temperature variation trend is determined according to the current furnace temperature index as If the temperature increases or decreases, then the final result is determined to be the temperature increase or the temperature decreases. If the current furnace temperature index is zero, the current furnace temperature index is changed to the next one in order of priority from high to low. Furnace temperature index, and determine the change trend of blast furnace temperature according to the current furnace temperature index again, and so on, until it is determined that the change trend of blast furnace temperature is temperature increase or temperature decrease, or determine the blast furnace temperature according to the last furnace temperature index The change trend is to keep the temperature within a reasonable range.

In the embodiment of the present invention, another method is proposed based on the first furnace temperature index and at least one of the determined second furnace temperature index, third furnace temperature index, fourth furnace temperature index and fifth furnace temperature index to determine The scheme of the changing trend of the blast furnace temperature, here, taking the determination of the changing trend of the blast furnace temperature based on the five furnace temperature indices as an example, as shown in Figure 7, may include the following processing steps

Step 71: Based on the first furnace temperature index, the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index, and the weights corresponding to each furnace temperature index, perform weighted summation to obtain the furnace temperature index Temperature Composite Index.

The following formula can be used:

Index＝μ1*Index1+μ2*Index2+μ3*Index3+μ4*Index4+μ5*Index5;

Among them, Index is the comprehensive index of furnace temperature, Index1, Index2, Index3, Index4 and Index5 are respectively the first furnace temperature index, the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index, μ1, μ2, μ3, μ4 and μ5 are the weights corresponding to the first furnace temperature index, the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index respectively, and μ1, μ2, μ3 The sum of , μ4 and μ5 is 1.

Step 72 : Determine whether the furnace temperature comprehensive index is greater than the first furnace temperature index threshold, if so, go to step 73 , otherwise, go to step 74 .

The first furnace temperature index threshold is greater than zero and smaller than a first preset furnace temperature index.

Step 73, determining that the change trend of the blast furnace temperature is temperature rise.

Step 74 , determine whether the comprehensive furnace temperature index is less than the second furnace temperature index threshold, if so, go to step 75 , otherwise, go to step 76 .

The second furnace temperature index threshold is greater than a second preset furnace temperature index and less than zero.

Step 75, determining that the change trend of the blast furnace temperature is temperature decrease.

Step 76, determining the temperature change trend of the blast furnace to keep the temperature within a reasonable range.

In the process shown in Figure 7 above, the first furnace temperature index threshold and the second furnace temperature index threshold can be flexibly set according to actual needs, for example, the first furnace temperature index threshold can be 0.5 times the first preset furnace temperature index , the second furnace temperature index threshold may be 0.5 times the second preset furnace temperature index.

For the convenience of calculation, in the embodiment of the present invention, the second preset furnace temperature index can be the negative first preset furnace temperature index, for example, the first preset furnace temperature index can be 1, and correspondingly, the second preset furnace temperature index can be 1. The temperature index is -1.

Using the above method provided by the embodiment of the present invention, compared with the manual judgment in the prior art, it is possible to more accurately determine the variation trend of the blast furnace temperature, and when the determination is based on the above-mentioned various furnace temperature indices, the accuracy of determination can be further improved sex.

Based on the same inventive concept, according to the method for determining the variation trend of the blast furnace temperature provided by the above-mentioned embodiments of the present invention, another embodiment of the present invention also provides a device for determining the variation trend of the blast furnace temperature, the structural diagram of which is shown in Figure 8 , specifically include:

An image acquisition unit 81, configured to acquire an image obtained by taking pictures of the blast furnace tuyere swirl area;

The temperature and brightness determining unit 82 is used to determine the flame temperature and the relative brightness of the flame in the tuyere swirl area in the image based on the pixel values of the pixel points in the image by means of radiation thermometry;

The first furnace temperature index determining unit 83 is used to determine that the first furnace temperature index is the first preset furnace when the flame temperature is greater than the first flame temperature threshold and the relative brightness of the flame is greater than the first flame relative brightness threshold temperature index, the first preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature increase; and

When the flame temperature is less than the second flame temperature threshold and the flame relative brightness is less than the second flame relative brightness threshold, it is determined that the first furnace temperature index is the second preset furnace temperature index, wherein the first The flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the furnace temperature of the blast furnace tends to decrease in temperature; and

Otherwise, it is determined that the first furnace temperature index is zero, indicating that the furnace temperature change trend of the blast furnace is to keep the temperature within a reasonable range;

A change trend determining unit 84, configured to determine a change trend of the blast furnace temperature based on the first furnace temperature index.

Further, it also includes:

At least one of the second furnace temperature index determination unit 85, the third furnace temperature index determination unit 86, the fourth furnace temperature index determination unit 87 and the fifth furnace temperature index determination unit 88;

Wherein, the second furnace temperature index determining unit 85 is used to determine the second furnace temperature index by adopting the following steps:

Determine the edge temperature index and central temperature index of the blast furnace throat, wherein the edge temperature index represents the situation of the edge temperature of the blast furnace throat relative to the average temperature of the blast furnace throat, and the central temperature index represents the relative temperature of the center temperature of the blast furnace throat The condition of the average temperature of the furnace throat;

When the edge temperature index is greater than the first edge temperature index threshold and the center temperature index is greater than the first center temperature index threshold, determine that the second furnace temperature index is the first preset furnace temperature index;

When the edge temperature index is less than the second edge temperature index threshold and the center temperature index is less than the second center temperature index threshold, the second furnace temperature index is determined to be the second preset furnace temperature index, wherein, the first edge temperature index threshold is greater than the second edge temperature index threshold, and the first core temperature index threshold is greater than the second core temperature index threshold;

Otherwise, determine that the second furnace temperature index is zero;

The third furnace temperature index determination unit 86 is used to determine the third furnace temperature index by adopting the following steps:

Determining the blanking acceleration corresponding to each of the multiple probes, and the acceleration standard deviation of the blanking acceleration corresponding to each of the multiple probes;

When for each probe, the feeding acceleration corresponding to the probe is less than the negative value of the sum of the first speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the first preset furnace temperature index;

When for each probe, the feeding acceleration corresponding to the probe is greater than the sum of the second speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the second preset furnace temperature index ;

Otherwise, determine that the third furnace temperature index is zero;

The fourth furnace temperature index determining unit 87 is configured to determine the fourth furnace temperature index by adopting the following steps:

Obtain the temperature of the blast furnace wall at multiple different heights in the blast furnace wall, and the temperature of the outer surface of the stave at the multiple different heights;

Based on the temperature of the blast furnace wall at the multiple different heights and the temperature of the outer surface of the stave, and according to the two-dimensional heat transfer mechanism model of the cross section of the blast furnace wall, determine the inner surface temperature of the blast furnace at the multiple different heights;

When for each height, the blast furnace inner surface temperature at the height is greater than the first blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the first preset furnace temperature index;

When for each height, the blast furnace inner surface temperature at that height is less than the second blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the second preset furnace temperature index, wherein, for each height, the temperature threshold of the first blast furnace inner surface corresponding to the height is greater than the second blast furnace inner surface temperature threshold corresponding to the height;

Otherwise, determine that the fourth temperature index is zero;

The fifth furnace temperature index determination unit 88 is configured to determine the fifth furnace temperature index by the following steps:

Obtain the current values of various input parameters required to determine the silicon content of the blast furnace hot metal based on the silicon content prediction model of the molten iron;

Determining the silicon content of the blast furnace molten iron according to the obtained current values of the various input parameters and according to the prediction model for the silicon content of the molten iron;

When the silicon content of the blast furnace hot metal is greater than the first preset blast furnace silicon threshold, the fifth furnace temperature index is determined as the first preset furnace temperature index;

When the silicon content of the blast furnace molten iron is less than the second preset blast furnace silicon threshold, the fifth furnace temperature index is determined to be the second preset furnace temperature index, wherein the first preset blast furnace silicon threshold is greater than The second preset blast furnace molten iron silicon threshold;

Otherwise, determine that the fifth furnace temperature index is zero;

The change trend determination unit 84 is specifically configured to determine the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the first furnace temperature index based on the first furnace temperature index and the determined At least one of the five furnace temperature indices determines the variation trend of the blast furnace temperature.

Further, the edge temperature index is the sum of the edge temperatures obtained by cross-measurement of the blast furnace throat, divided by four times the average top temperature of the throat temperature obtained by the cross-measurement;

The central temperature index is the sum of the central temperature obtained by performing the cross temperature measurement and the temperature of the four points close to the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement; or, The center temperature index is the sum of the center temperature obtained by performing the cross temperature measurement and the temperature of the four points near the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement and the preset The product of constants, the preset constant is greater than 1.

Further, the fifth furnace temperature index determination unit 88 is also used to determine the silicon content prediction model of molten iron by adopting the following steps:

In the preset time period, according to the preset time interval, various input parameter values of the molten iron silicon content prediction model are collected, and the multiple values of each input parameter collected are normalized respectively, and the normalized Various input parameter values of ;

During the preset time period, at the moment when the blast furnace molten iron is produced, the silicon content of the molten iron in the blast furnace produced at this time is collected;

Based on the silicon content of molten iron collected multiple times, curve fitting is performed according to the time axis to obtain a silicon content curve of molten iron within the preset time period;

Determining the silicon content of molten iron corresponding to each sampling moment according to the preset time interval in the silicon content curve of the molten iron;

Based on the normalized various input parameter values and the determined silicon content of molten iron corresponding to each sampling time interval according to the preset time interval, a prediction model of silicon content in molten iron is established according to a support vector regression method.

Further, the change trend determination unit 84 is specifically configured to determine based on the first furnace temperature index, the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and At least one of the fifth furnace temperature index and the weights corresponding to each furnace temperature index are weighted and summed to obtain a comprehensive furnace temperature index;

When the comprehensive furnace temperature index is greater than the first furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is temperature rise, and the first furnace temperature index threshold is greater than zero and less than the first preset furnace temperature index;

When the comprehensive furnace temperature index is less than the second furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is a temperature decrease, and the second furnace temperature index threshold is greater than the second preset furnace temperature index and less than zero, so The second preset furnace temperature index is negative for the first preset furnace temperature index;

Otherwise, determine the variation trend of blast furnace temperature to keep the temperature within a reasonable range.

The functions of the above units may correspond to the corresponding processing steps in the flow shown in FIG. 1 to FIG. 7 , which will not be repeated here.

To sum up, the solution provided by the embodiment of the present invention includes: obtaining an image obtained by photographing the tuyere swirl of the blast furnace; flame temperature and flame relative brightness; and when the flame temperature is greater than the first flame temperature threshold, and the flame relative brightness is greater than the first flame relative brightness threshold, it is determined that the first furnace temperature index is the first preset furnace temperature index, and the first preset furnace temperature index is determined to be the first preset furnace temperature index. Let the furnace temperature index indicate that the temperature change trend of the blast furnace is temperature rise; when the flame temperature is less than the second flame temperature threshold and the relative brightness of the flame is smaller than the second flame relative brightness threshold, the first furnace temperature index is determined to be the second preset furnace Temperature index, wherein, the first flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the temperature change trend of the blast furnace is a decrease in temperature; otherwise, Determining that the first furnace temperature index is zero indicates that the change trend of the blast furnace temperature is to keep the temperature within a reasonable range, and based on the first furnace temperature index, determine the change trend of the blast furnace temperature. By adopting the solution provided by the embodiment of the present invention, the temperature variation trend of the blast furnace can be determined more accurately.

The device for determining the variation trend of the blast furnace temperature provided by the embodiments of the present application can be realized by a computer program. Those skilled in the art should be able to understand that the above-mentioned module division method is only one of many module division methods. If it is divided into other modules or not divided into modules, as long as the blast furnace temperature change trend determination device has the above functions, it should be in this within the scope of the application.

The present application is described with reference to flowcharts and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow diagram procedure or procedures and/or block diagram procedures or blocks.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims (10)

1. A method for determining the variation trend of blast furnace temperature, characterized in that, comprising: Obtain the image obtained by taking pictures of the tuyere swirl area of the blast furnace; Based on the pixel value of the pixel point in the image, the temperature of the flame and the relative brightness of the flame in the tuyere swirl area in the image are determined by using a radiation thermometry method; When the flame temperature is greater than the first flame temperature threshold and the flame relative brightness is greater than the first flame relative brightness threshold, the first furnace temperature index is determined to be the first preset furnace temperature index, and the first preset furnace temperature The index indicates that the temperature change trend of the blast furnace is temperature increase; When the flame temperature is less than the second flame temperature threshold and the flame relative brightness is less than the second flame relative brightness threshold, it is determined that the first furnace temperature index is the second preset furnace temperature index, wherein the first The flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the temperature change trend of the blast furnace is temperature decrease; Otherwise, it is determined that the first furnace temperature index is zero, indicating that the furnace temperature change trend of the blast furnace is to keep the temperature within a reasonable range; Based on the first furnace temperature index, the variation trend of the furnace temperature of the blast furnace is determined. 2. The method according to claim 1, further comprising: before determining the variation trend of blast furnace temperature based on the first furnace temperature index: determining at least one of the second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index; Wherein, adopt the following steps to determine the second furnace temperature index: Determine the edge temperature index and central temperature index of the blast furnace throat, wherein the edge temperature index represents the situation of the edge temperature of the blast furnace throat relative to the average temperature of the blast furnace throat, and the central temperature index represents the relative temperature of the center temperature of the blast furnace throat The condition of the average temperature of the furnace throat; When the edge temperature index is greater than the first edge temperature index threshold and the center temperature index is greater than the first center temperature index threshold, determine that the second furnace temperature index is the first preset furnace temperature index; When the edge temperature index is less than the second edge temperature index threshold and the center temperature index is less than the second center temperature index threshold, the second furnace temperature index is determined to be the second preset furnace temperature index, wherein, the first edge temperature index threshold is greater than the second edge temperature index threshold, and the first core temperature index threshold is greater than the second core temperature index threshold; Otherwise, determine that the second furnace temperature index is zero; Adopt the following steps to determine the third furnace temperature index: Determining the blanking acceleration corresponding to each of the multiple probes, and the acceleration standard deviation of the blanking acceleration corresponding to each of the multiple probes; When for each probe, the feeding acceleration corresponding to the probe is less than the negative value of the sum of the first speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the first preset furnace temperature index; When for each probe, the feeding acceleration corresponding to the probe is greater than the sum of the second speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the second preset furnace temperature index ; Otherwise, determine that the third furnace temperature index is zero; The following steps are adopted to determine the fourth furnace temperature index: Obtain the temperature of the blast furnace wall at multiple different heights in the blast furnace wall, and the temperature of the outer surface of the stave at the multiple different heights; Based on the temperature of the blast furnace wall at the multiple different heights and the temperature of the outer surface of the stave, and according to the two-dimensional heat transfer mechanism model of the cross section of the blast furnace wall, determine the inner surface temperature of the blast furnace at the multiple different heights; When for each height, the blast furnace inner surface temperature at the height is greater than the first blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the first preset furnace temperature index; When for each height, the blast furnace inner surface temperature at that height is less than the second blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the second preset furnace temperature index, wherein, for each height, the temperature threshold of the first blast furnace inner surface corresponding to the height is greater than the second blast furnace inner surface temperature threshold corresponding to the height; Otherwise, determine that the fourth temperature index is zero; Use the following steps to determine the fifth furnace temperature index: Obtain the current values of various input parameters required to determine the silicon content of the blast furnace hot metal based on the silicon content prediction model of the molten iron; Determining the silicon content of the blast furnace molten iron according to the obtained current values of the various input parameters and according to the prediction model for the silicon content of the molten iron; When the silicon content of the blast furnace hot metal is greater than the first preset blast furnace silicon threshold, the fifth furnace temperature index is determined as the first preset furnace temperature index; When the silicon content of the blast furnace molten iron is less than the second preset blast furnace silicon threshold, the fifth furnace temperature index is determined to be the second preset furnace temperature index, wherein the first preset blast furnace silicon threshold is greater than The second preset blast furnace molten iron silicon threshold; Otherwise, determine that the fifth furnace temperature index is zero; Based on the first furnace temperature index, determining the variation trend of the blast furnace temperature includes: Determine the blast furnace based on the first furnace temperature index and at least one of the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index Variation trend of furnace temperature. 3. The method according to claim 2, wherein the edge temperature index is the sum of the edge temperatures obtained by cross-measuring the blast furnace throat, divided by the throat temperature obtained by performing the cross-measuring 4 times the average top temperature; The central temperature index is the sum of the central temperature obtained by performing the cross temperature measurement and the temperature of the four points close to the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement; or, The center temperature index is the sum of the center temperature obtained by performing the cross temperature measurement and the temperature of the four points near the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement and the preset The product of constants, the preset constant is greater than 1. 4. method as claimed in claim 2, is characterized in that, adopts the following steps to determine described molten iron silicon content prediction model: In the preset time period, according to the preset time interval, various input parameter values of the molten iron silicon content prediction model are collected, and the multiple values of each input parameter collected are normalized respectively, and the normalized Various input parameter values of ; During the preset time period, at the moment when the blast furnace molten iron is produced, the silicon content of the molten iron in the blast furnace produced at this time is collected; Based on the silicon content of molten iron collected multiple times, curve fitting is performed according to the time axis to obtain a silicon content curve of molten iron within the preset time period; Determining the silicon content of molten iron corresponding to each sampling moment according to the preset time interval in the silicon content curve of the molten iron; Based on the normalized various input parameter values and the determined silicon content of molten iron corresponding to each sampling time interval according to the preset time interval, a prediction model of silicon content in molten iron is established according to a support vector regression method. 5. The method according to any one of claims 2-4, characterized in that, based on the first furnace temperature index, and the determined second furnace temperature index, the third furnace temperature index, the first At least one of the four furnace temperature indices and the fifth furnace temperature index determines the variation trend of the blast furnace temperature, specifically including: Based on the first furnace temperature index, and at least one of the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index, and each The weight corresponding to the furnace temperature index is weighted and summed to obtain the comprehensive furnace temperature index; When the comprehensive furnace temperature index is greater than the first furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is temperature rise, and the first furnace temperature index threshold is greater than zero and less than the first preset furnace temperature index; When the comprehensive furnace temperature index is less than the second furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is a temperature decrease, and the second furnace temperature index threshold is greater than the second preset furnace temperature index and less than zero, so The second preset furnace temperature index is negative for the first preset furnace temperature index; Otherwise, determine the variation trend of blast furnace temperature to keep the temperature within a reasonable range. 6. A blast furnace temperature variation trend determining device, characterized in that it comprises: an image acquisition unit, configured to acquire an image obtained by taking pictures of the blast furnace tuyere swirl; The temperature and brightness determination unit is used to determine the flame temperature and the relative brightness of the flame in the tuyere swirl area in the image based on the pixel values of the pixel points in the image by means of radiation thermometry; The first furnace temperature index determining unit is configured to determine the first furnace temperature index as the first preset furnace temperature when the flame temperature is greater than the first flame temperature threshold and the relative brightness of the flame is greater than the first flame relative brightness threshold index, the first preset furnace temperature index indicates that the temperature change trend of the blast furnace is a temperature increase; and When the flame temperature is less than the second flame temperature threshold and the flame relative brightness is less than the second flame relative brightness threshold, it is determined that the first furnace temperature index is the second preset furnace temperature index, wherein the first The flame temperature threshold is greater than the second flame temperature threshold, the first flame relative brightness threshold is greater than the second flame relative brightness threshold, and the second preset furnace temperature index indicates that the furnace temperature of the blast furnace tends to decrease in temperature; and Otherwise, it is determined that the first furnace temperature index is zero, indicating that the furnace temperature change trend of the blast furnace is to keep the temperature within a reasonable range; The change trend determination unit is configured to determine the change trend of the blast furnace temperature based on the first furnace temperature index. 7. The device of claim 6, further comprising: At least one of the second furnace temperature index determination unit, the third furnace temperature index determination unit, the fourth furnace temperature index determination unit and the fifth furnace temperature index determination unit; Wherein, the second furnace temperature index determination unit is used to determine the second furnace temperature index by adopting the following steps: Determine the edge temperature index and central temperature index of the blast furnace throat, wherein the edge temperature index represents the situation of the edge temperature of the blast furnace throat relative to the average temperature of the blast furnace throat, and the central temperature index represents the relative temperature of the center temperature of the blast furnace throat The condition of the average temperature of the furnace throat; When the edge temperature index is greater than the first edge temperature index threshold and the center temperature index is greater than the first center temperature index threshold, determine that the second furnace temperature index is the first preset furnace temperature index; When the edge temperature index is less than the second edge temperature index threshold and the center temperature index is less than the second center temperature index threshold, the second furnace temperature index is determined to be the second preset furnace temperature index, wherein, the first edge temperature index threshold is greater than the second edge temperature index threshold, and the first core temperature index threshold is greater than the second core temperature index threshold; Otherwise, determine that the second furnace temperature index is zero; The third furnace temperature index determining unit is configured to determine the third furnace temperature index by adopting the following steps: Determining the blanking acceleration corresponding to each of the multiple probes, and the acceleration standard deviation of the blanking acceleration corresponding to each of the multiple probes; When for each probe, the feeding acceleration corresponding to the probe is less than the negative value of the sum of the first speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the first preset furnace temperature index; When for each probe, the feeding acceleration corresponding to the probe is greater than the sum of the second speed threshold and the acceleration standard deviation, determine the third furnace temperature index as the second preset furnace temperature index ; Otherwise, determine that the third furnace temperature index is zero; The fourth furnace temperature index determination unit is used to determine the fourth furnace temperature index by adopting the following steps: Obtain the temperature of the blast furnace wall at multiple different heights in the blast furnace wall, and the temperature of the outer surface of the stave at the multiple different heights; Based on the temperature of the blast furnace wall at the multiple different heights and the temperature of the outer surface of the stave, and according to the two-dimensional heat transfer mechanism model of the cross section of the blast furnace wall, determine the inner surface temperature of the blast furnace at the multiple different heights; When for each height, the blast furnace inner surface temperature at the height is greater than the first blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the first preset furnace temperature index; When for each height, the blast furnace inner surface temperature at that height is less than the second blast furnace inner surface temperature threshold corresponding to the height, determine the fourth furnace temperature index as the second preset furnace temperature index, wherein, for each height, the temperature threshold of the first blast furnace inner surface corresponding to the height is greater than the second blast furnace inner surface temperature threshold corresponding to the height; Otherwise, determine that the fourth temperature index is zero; The fifth furnace temperature index determining unit is configured to determine the fifth furnace temperature index by adopting the following steps: Obtain the current values of various input parameters required to determine the silicon content of the blast furnace hot metal based on the silicon content prediction model of the molten iron; Determining the silicon content of the blast furnace molten iron according to the obtained current values of the various input parameters and according to the prediction model for the silicon content of the molten iron; When the silicon content of the blast furnace hot metal is greater than the first preset blast furnace silicon threshold, the fifth furnace temperature index is determined as the first preset furnace temperature index; When the silicon content of the blast furnace molten iron is less than the second preset blast furnace silicon threshold, the fifth furnace temperature index is determined to be the second preset furnace temperature index, wherein the first preset blast furnace silicon threshold is greater than The second preset blast furnace molten iron silicon threshold; Otherwise, determine that the fifth furnace temperature index is zero; The change trend determining unit is specifically configured to be based on the first furnace temperature index, and the determined second furnace temperature index, the third furnace temperature index, the fourth furnace temperature index and the fifth furnace temperature index. At least one of the furnace temperature indices determines the variation trend of the blast furnace temperature. 8. The device according to claim 7, characterized in that, the edge temperature index is the sum of the edge temperatures obtained by cross-measuring the blast furnace throat, divided by the throat temperature obtained by performing the cross-measuring 4 times the average top temperature; The central temperature index is the sum of the central temperature obtained by performing the cross temperature measurement and the temperature of the four points close to the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement; or, The center temperature index is the sum of the center temperature obtained by performing the cross temperature measurement and the temperature of the four points near the center, divided by 5 times the average top temperature of the furnace throat temperature obtained by performing the cross temperature measurement and the preset The product of constants, the preset constant is greater than 1. 9. The device according to claim 7, characterized in that, the fifth furnace temperature index determination unit is also used to determine the silicon content prediction model of molten iron by adopting the following steps: In the preset time period, according to the preset time interval, various input parameter values of the molten iron silicon content prediction model are collected, and the multiple values of each input parameter collected are normalized respectively, and the normalized Various input parameter values of ; During the preset time period, at the moment when the blast furnace molten iron is produced, the silicon content of the molten iron in the blast furnace produced at this time is collected; Based on the silicon content of molten iron collected multiple times, curve fitting is performed according to the time axis to obtain a silicon content curve of molten iron within the preset time period; Determining the silicon content of molten iron corresponding to each sampling moment according to the preset time interval in the silicon content curve of the molten iron; Based on the normalized various input parameter values and the determined silicon content of molten iron corresponding to each sampling time interval according to the preset time interval, a prediction model of silicon content in molten iron is established according to a support vector regression method. 10. The device according to any one of claims 7-9, wherein the change trend determining unit is specifically configured to be based on the first furnace temperature index, the determined second furnace temperature index, the determined At least one of the third furnace temperature index, the fourth furnace temperature index, and the fifth furnace temperature index, and the weights corresponding to each furnace temperature index, are weighted and summed to obtain the comprehensive furnace temperature index; When the comprehensive furnace temperature index is greater than the first furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is temperature rise, and the first furnace temperature index threshold is greater than zero and less than the first preset furnace temperature index; When the comprehensive furnace temperature index is less than the second furnace temperature index threshold, it is determined that the change trend of the blast furnace temperature is a temperature decrease, and the second furnace temperature index threshold is greater than the second preset furnace temperature index and less than zero, so The second preset furnace temperature index is negative for the first preset furnace temperature index; Otherwise, determine the variation trend of blast furnace temperature to keep the temperature within a reasonable range.