CN115597715A - Blast furnace soft cross temperature measurement method based on infrared temperature measurement - Google Patents
Blast furnace soft cross temperature measurement method based on infrared temperature measurement Download PDFInfo
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Abstract
The invention relates to the field of blast furnace metallurgy, and discloses a blast furnace soft cross temperature measurement method based on infrared temperature measurement. The method comprises the following steps: firstly, a cross temperature measuring device and an infrared temperature measuring device are installed on a blast furnace, and virtual cross temperature measuring points on an infrared image are determined according to the position mapping relation between pixel points of the infrared image and the cross temperature measuring points; training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point according to the temperature value of the virtual cross temperature measuring point and the temperature value of the cross temperature measuring point; the model is then used to calculate a predicted temperature value for the cross temperature measurement point on a blast furnace with only infrared temperature measurements installed. By adopting the method, a traditional cross temperature measuring device is not required to be installed, the temperature measuring result of the original infrared image is converted into the temperature value of a cross temperature measuring point, and the corresponding blast furnace operation and decision are executed by utilizing the existing cross temperature measuring temperature model.
Description
Technical Field
The invention relates to the field of blast furnace ironmaking in the metallurgical industry, in particular to a blast furnace soft cross temperature measurement method based on infrared temperature measurement.
Background
The cross temperature measuring device is positioned at the furnace throat of the blast furnace, four temperature measuring arms are arranged in four directions on the circumferential surface of the furnace throat, each temperature measuring arm is provided with unequal temperature sensors (such as thermocouples) and a total of 17-21 temperature measuring sensors, and the temperature measuring points can provide real-time temperature data and can relatively comprehensively reflect the distribution of the gas flow in the circumferential direction of the furnace throat. The cross temperature measuring device is arranged at the top of the closed blast furnace barrel, and the operation environment is extremely severe. Therefore, the cross temperature measuring device sensor is easy to damage, cannot be maintained in time after being damaged, and can be replaced only by long-term blast furnace overhaul.
The non-contact infrared thermal imaging temperature measurement method is developed in the 90 s of the 20 th century, is widely applied to the temperature measurement of the top of a blast furnace at present, and can observe the spatial temperature field distribution in the blast furnace. Because the thermal imaging sensing element infrared focal plane array does not need to be contacted with a space target in the furnace, the temperature field distribution and the service life of the sensor are not influenced. The infrared radiation is used for measuring the temperature, and the infrared radiation temperature measuring device has the advantages of quick response, long service life of the sensor, non-consumption, high measuring temperature and capability of realizing real-time continuous measurement.
According to the infrared radiation temperature measurement principle, the temperature measurement result has a great relation with the radiance of a target object, when the radiance of the infrared detector is set to be 0.97 through actual measurement data, the temperature result measured by the infrared detector is far lower than the cross temperature measurement result, so that an operator cannot directly replace the cross temperature measurement with the temperature measurement result of an original infrared image, and corresponding blast furnace operation and decision are executed by using the existing temperature model of the cross temperature measurement.
Disclosure of Invention
In view of the above-mentioned defects of the prior art, the present invention is to combine the furnace top infrared temperature measurement technology with the cross temperature measurement technology, without installing the traditional cross temperature measurement device, convert the temperature measurement result of the original infrared image into the temperature value of the set cross temperature measurement point, and utilize the existing cross temperature measurement temperature model to execute the corresponding blast furnace operation and decision.
In order to achieve the aim, the invention provides a blast furnace soft cross temperature measurement method based on infrared temperature measurement, which comprises the following steps:
step S10, arranging an infrared temperature measuring device and a cross temperature measuring device on the blast furnace at the same time; determining a virtual cross temperature measuring point on the infrared image according to the position mapping relation between the pixel point of the infrared image and the cross temperature measuring point; training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point according to the temperature value of the virtual cross temperature measuring point and the temperature value of the cross temperature measuring point;
step S20, only arranging an infrared temperature measuring device on the blast furnace; setting the positions of the cross temperature measuring points, and determining virtual cross temperature measuring points on the infrared image according to the position mapping relation between pixel points of the infrared image and the cross temperature measuring points; and extracting the temperature value of the virtual cross temperature measuring point from the infrared image, and outputting the predicted temperature value of the cross temperature measuring point through a temperature relation model.
Further, the step S10 includes:
step S101: simultaneously installing a cross temperature measuring device and an infrared temperature measuring device on the blast furnace;
step S102: establishing a plane coordinate system of the blast furnace according to the installation plane of the cross temperature measuring device in the furnace;
step S103: establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I1 into a bird's-eye view temperature image I2 located in a plane coordinate system of the blast furnace;
step S104: according to the installation position of the cross temperature measuring device in the furnace, finding out corresponding pixel point coordinates in the bird's-eye view temperature image I2, finding out corresponding pixel point coordinates in the infrared image I1 through the pixel point coordinates, and establishing a virtual cross temperature measuring point;
step S105: reading the temperature value of the virtual cross temperature measuring point to form a first temperature sequence;
step S106: reading the temperature value of the cross temperature measuring point through a cross temperature measuring device to form a second temperature sequence;
step S107: and training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point by taking the first temperature sequence as input and the second temperature sequence as output.
Further, in step S10, in the plane coordinate system of the blast furnace, the origin of coordinates of the top of the blast furnace is set to be located at the center of the blast furnace on the horizontal plane where the temperature measuring point of the cross temperature measuring device is located.
Further, the step S103 includes:
selecting coordinates of four points on the circumference of a furnace shell in the blast furnace as A (-R, 0), B (R.0), C (0,R) and D (0, -R), wherein R is the inner diameter of the blast furnace, and the coordinates of the four points on an infrared image are calculated by calculating upper, lower, left and right boundary points through manual measurement or an image algorithm to obtain A '(XA, YA), B' (XB, YB), C '(XC, YC) and D' (XD, YD);
and calculating a perspective transformation matrix P1 from a blast furnace coordinate system to an infrared image I1 coordinate system according to a perspective transformation principle, and obtaining a bird's-eye view temperature image I2 obtained by converting the original infrared image I1 into a horizontal coordinate system of the blast furnace according to the perspective transformation matrix.
Further, in step S107, the temperature relationship model is based on an MLP neural network model.
Further, the step S20 includes:
step S201: installing an infrared temperature measuring device on the top of the blast furnace to obtain an infrared image of the top of the blast furnace;
step S202: establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I3 into a bird's-eye view temperature image I4 located in a plane coordinate system of the blast furnace;
step S203: setting the position of a cross temperature measuring point;
step S204: finding pixel point coordinates corresponding to the cross temperature measuring points from the bird's-eye view temperature image I4, and establishing virtual cross temperature measuring points in the infrared image I3 through a perspective transformation matrix;
step S205: extracting the temperature value of the virtual cross temperature measuring point to form a third temperature sequence;
step S206: and inputting the third temperature sequence into a trained temperature relation model of the virtual cross temperature measuring points and the real cross temperature measuring points, and outputting a fourth temperature sequence consisting of predicted temperature values of all the cross temperature measuring points.
The invention realizes the following technical effects:
by adopting the method, a traditional cross temperature measuring device is not required to be installed, an original infrared image is obtained through the infrared temperature measuring device, the temperature measuring result of the original infrared image is converted into the temperature value of a cross temperature measuring point, and corresponding blast furnace operation and decision are executed by utilizing the existing cross temperature measuring temperature model.
Drawings
FIG. 1 is a flow chart of a blast furnace soft cross temperature measurement method based on infrared temperature measurement;
FIG. 2 is a position map of an infrared image and a bird's eye view temperature image of the present invention;
fig. 3 is a neural network model according to the present invention.
Detailed Description
To further illustrate the various embodiments, the invention provides the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the embodiments. With these references, one of ordinary skill in the art will appreciate other possible embodiments and advantages of the present invention.
The invention will now be further described with reference to the accompanying drawings and detailed description.
As shown in FIG. 1, the application provides a blast furnace soft cross temperature measurement method based on infrared temperature measurement, which comprises the following steps:
step S10, arranging an infrared temperature measuring device and a cross temperature measuring device on the blast furnace at the same time; determining a virtual cross temperature measuring point on the infrared image according to the position mapping relation between the pixel point of the infrared image and the cross temperature measuring point; and training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point according to the temperature value of the virtual cross temperature measuring point and the temperature value of the cross temperature measuring point.
Step S20, only arranging an infrared temperature measuring device on the blast furnace; setting the positions of the cross temperature measuring points, and determining the positions of the virtual cross temperature measuring points on the infrared image according to the position mapping relation between the pixel points of the infrared image and the cross temperature measuring points; and extracting the temperature value of the virtual cross temperature measuring point from the infrared image, and outputting the predicted temperature value of the cross temperature measuring point through a temperature relation model.
Specifically, step S10 includes:
simultaneously installing a cross temperature measuring device and an infrared temperature measuring device on the blast furnace; establishing a plane coordinate system of the blast furnace according to the installation plane of the cross temperature measuring device in the furnace; establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I1 into a bird's-eye view temperature image I2 located in a plane coordinate system of the blast furnace; and finding out corresponding pixel point coordinates in the bird's-eye view temperature image I2 according to the installation position of the cross temperature measuring device in the furnace, and establishing a virtual cross temperature measuring point according to the pixel point coordinates. Reading the temperature value of the virtual cross temperature measuring point to form a first temperature sequence; and reading the temperature value of the cross temperature measuring point through the cross temperature measuring device to form a second temperature sequence.
Specifically, in this embodiment, a specific implementation scheme of the above steps is given: because the infrared temperature measuring camera can not be arranged on the central line of the top of the blast furnace and is completely parallel to the horizontal plane for taking a picture, but is arranged on the side wall of the blast furnace and forms a certain included angle with the horizontal plane, the concentric circle pattern of the cross temperature measurement is not a circle on the infrared image, but a pattern formed by perspective transformation of the concentric circle, as shown in fig. 2. Therefore, the first step needs to solve the perspective transformation matrix P from the actual coordinates of the blast furnace to the coordinates of the infrared image.
Establishing a blast furnace coordinate system, and setting the origin of blast furnace top coordinates on the center of a blast furnace of a cross temperature measuring device installation plane (namely, a horizontal plane where temperature measuring points of the cross temperature measuring device are located), as shown in fig. 2, coordinates of four points on the circumference of a furnace shell in the blast furnace are A (-R, 0), B (R.0), C (0,R), and D (0, -R), wherein R is the inner diameter of the blast furnace, and coordinates of the four points on an infrared image can be calculated by manual measurement or an image algorithm to obtain boundary points of the upper left and the lower right to obtain A '(XA, YA), B' (XB, YB), C '(XC, YC), D' (XD, YD), wherein the point of the upper left corner of the image is used as the origin. According to the perspective transformation principle, a perspective transformation matrix P1 from a blast furnace coordinate system to an infrared image I1 coordinate system can be calculated, and a bird's-eye view temperature image I2 of the original infrared image I1 converted to a horizontal coordinate system of the blast furnace can be obtained according to the perspective transformation matrix.
Therefore, a virtual cross temperature measurement scheme can be designed, for example, a temperature measurement point is arranged in 4 directions of 0 degrees, 90 degrees, 180 degrees and 270 degrees at intervals of 0.8 meter, and 5 points are arranged in each direction. The coordinates of the temperature measuring points are as follows:
its corresponding point on the infrared image I3 is
The virtual cross temperature measurement scheme can adopt the original cross temperature measurement scheme, thereby facilitating blast furnace operation and decision by utilizing the original temperature model. It is also possible to set a new cross temperature scheme and train a new temperature model to support blast furnace operation and decision making.
And then calculating a conversion relation between the temperatures of the two layers, considering that the conversion relation between the two layers is possibly nonlinear, designing a neural network model comprising a plurality of hidden layers to represent the relation, wherein an input layer of the network is an infrared temperature measurement result, an output layer is a temperature measurement result of a fitted corresponding cross temperature measurement point, the network comprises 2 hidden layers, and each hidden layer comprises 10 nodes, as shown in fig. 3.
In this embodiment, the following training scheme of a temperature relationship model between a virtual cross temperature measurement point and a real cross temperature measurement point is provided: 20 cross temperature measuring points and corresponding infrared temperature measuring results are respectively sampled at intervals of 2 hours to form sample data, and 12000 groups of sample data are sampled for 50 days in the embodiment to carry out cross validation and solving on the temperature correction network. We randomly used 80% of the data as a training set to train the temperature correction network, 10% of the data as a validation set to control the number of training cycles, and 10% of the data as a test set to test the generalization effect of the model. The loss function takes the Mean Squared Error sum (Mean Squared Error), which is defined as:
wherein
M is the number of samples in a certain sample set, and the sample set comprises a training set, a verification set and a test set;
T(k),T S (k) The real cross temperature measurement value measured in the kth group and the temperature measurement value output by the network are respectively.
And (5) training by adopting an Adam optimization algorithm after 100 cycles, terminating the training after the error change of the verification set tends to 0, and storing the weight and the bias parameter into a Model file Model.
In the specific implementation process, in order to realize the training of the temperature relation model of the virtual cross temperature measurement point and the real cross temperature measurement point, a neural network model such as an MLP (multi-layer perceptron) model can be adopted for training. The MLP multi-layered perceptron is an artificial neural network ANN of forward architecture that maps a set of input vectors to a set of output vectors. An MLP can be viewed as a directed graph, consisting of multiple layers of nodes, each layer being fully connected to the next. Except for the input nodes, each node is a neuron with a nonlinear activation function.
Specifically, step 20 includes:
step S201: an infrared temperature measuring device is arranged on the top of the blast furnace;
step S202: establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I3 into a bird's-eye view temperature image I4 located in a plane coordinate system of the blast furnace;
step S203: setting the position of a cross temperature measuring point;
step S204: finding pixel point coordinates corresponding to the cross temperature measuring points from the bird's-eye view temperature image I4, and establishing virtual cross temperature measuring points in the infrared image I3 through a perspective transformation matrix;
step S205: extracting the temperature values of the virtual cross temperature measuring points to form a third temperature sequence;
step S206: and inputting the third temperature sequence into a trained temperature relation model of the virtual cross temperature measuring points and the real cross temperature measuring points, and outputting a fourth temperature sequence consisting of predicted temperature values of all the cross temperature measuring points.
The fourth temperature sequence is the predicted temperature values of the cross temperature measuring points, and according to the predicted temperature values, corresponding blast furnace operation and decision can be executed by using the existing temperature model of cross temperature measurement.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A blast furnace soft cross temperature measurement method based on infrared temperature measurement is characterized by comprising the following steps:
step S10, arranging an infrared temperature measuring device and a cross temperature measuring device on the blast furnace at the same time; determining a virtual cross temperature measuring point on the infrared image according to the position mapping relation between the pixel points of the infrared image and the cross temperature measuring points; training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point according to the temperature value of the virtual cross temperature measuring point and the temperature value of the cross temperature measuring point;
step S20, only arranging an infrared temperature measuring device on the blast furnace; setting the positions of the cross temperature measuring points, and determining virtual cross temperature measuring points on the infrared image according to the position mapping relation between pixel points of the infrared image and the cross temperature measuring points; and extracting the temperature value of the virtual cross temperature measuring point from the infrared image, and outputting the predicted temperature value of the cross temperature measuring point through a temperature relation model.
2. The blast furnace soft cross temperature measurement method based on infrared temperature measurement as claimed in claim 1, wherein the step S10 includes:
step S101: simultaneously installing a cross temperature measuring device and an infrared temperature measuring device on the blast furnace;
step S102: establishing a plane coordinate system of the blast furnace according to the installation plane of the cross temperature measuring device in the furnace;
step S103: establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I1 into a bird's-eye view temperature image I2 located in a plane coordinate system of the blast furnace;
step S104: according to the installation position of the cross temperature measuring device in the furnace, pixel point coordinates corresponding to the cross temperature measuring point are found in the bird's-eye view temperature image I2, and the corresponding pixel point coordinates are found in the infrared image I1 through the pixel point coordinates to establish a virtual cross temperature measuring point;
step S105: reading the temperature value of the virtual cross temperature measuring point to form a first temperature sequence;
step S106: reading the temperature value of the cross temperature measuring point through a cross temperature measuring device to form a second temperature sequence;
step S107: and training a temperature relation model of the virtual cross temperature measuring point and the real cross temperature measuring point by taking the first temperature sequence as input and the second temperature sequence as output.
3. The soft cross temperature measurement method for blast furnace based on infrared temperature measurement as claimed in claim 2, wherein in step S10, the blast furnace plane coordinate system is set such that the blast furnace top coordinate origin is located at the center of the blast furnace in the plane of cross temperature measurement installation height.
4. The blast furnace soft cross temperature measurement method based on infrared temperature measurement as claimed in claim 3, wherein the step S103 comprises:
selecting coordinates of four points on the circumference of a furnace shell in the blast furnace as A (-R, 0), B (R.0), C (0,R) and D (0, -R), wherein R is the inner diameter of the blast furnace, and the coordinates of the four points on the infrared image are calculated by calculating upper, lower, left and right boundary points through manual measurement or an image algorithm to obtain A '(XA, YA), B' (XB, YB), C '(XC, YC) and D' (XD, YD);
and calculating a perspective transformation matrix P1 from a blast furnace coordinate system to an infrared image I1 coordinate system according to a perspective transformation principle, and obtaining a bird's-eye view temperature image I2 obtained by converting the original infrared image I1 into a horizontal coordinate system of the blast furnace according to the perspective transformation matrix.
5. The blast furnace soft-cross temperature measurement method based on infrared temperature measurement as claimed in claim 2, wherein in step S107, the temperature relation model is based on an MLP neural network model.
6. The blast furnace soft cross temperature measurement method based on infrared temperature measurement as claimed in claim 1, wherein the step S20 includes:
step S201: an infrared temperature measuring device is arranged on the top of the blast furnace;
step S202: establishing a perspective transformation matrix according to the installation position of the infrared temperature measuring device on the furnace top, and correcting the infrared image I3 into a bird's-eye view temperature image I4 located in a plane coordinate system of the blast furnace;
step S203: setting the position of a cross temperature measuring point;
step S204: finding pixel point coordinates corresponding to the cross temperature measuring points from the bird's-eye view temperature image I4, and establishing virtual cross temperature measuring points in the infrared image I3 through a perspective transformation matrix;
step S205: extracting the temperature value of the virtual cross temperature measuring point to form a third temperature sequence;
step S206: and inputting the third temperature sequence into a trained temperature relation model of the virtual cross temperature measurement points and the real cross temperature measurement points, and outputting a fourth temperature sequence consisting of predicted temperature values of all the cross temperature measurement points.
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| CN105002321B (en) * | 2015-06-16 | 2017-03-15 | 内蒙古科技大学 | A kind of gas treatment stream center dynamic tracking and gas utilization rate monitoring method |
| CN106227699B (en) * | 2016-07-04 | 2018-10-23 | 东北大学 | A kind of blast furnace throat cross temperature measurer center band temperature predicting method and system |
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