CN113468684A - Method and system for measuring temperature of melt in melting device - Google Patents
Method and system for measuring temperature of melt in melting device Download PDFInfo
- Publication number
- CN113468684A CN113468684A CN202110684262.4A CN202110684262A CN113468684A CN 113468684 A CN113468684 A CN 113468684A CN 202110684262 A CN202110684262 A CN 202110684262A CN 113468684 A CN113468684 A CN 113468684A
- Authority
- CN
- China
- Prior art keywords
- data
- melt
- stirring device
- temperature
- sample set
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
-
- C—CHEMISTRY; METALLURGY
- C03—GLASS; MINERAL OR SLAG WOOL
- C03B—MANUFACTURE, SHAPING, OR SUPPLEMENTARY PROCESSES
- C03B5/00—Melting in furnaces; Furnaces so far as specially adapted for glass manufacture
- C03B5/16—Special features of the melting process; Auxiliary means specially adapted for glass-melting furnaces
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Materials Engineering (AREA)
- Organic Chemistry (AREA)
- Waste-Gas Treatment And Other Accessory Devices For Furnaces (AREA)
Abstract
The invention discloses a method and a system for measuring the temperature of a melt in a melting device, wherein the melt in the melting device is continuously stirred by a stirring device, and the measuring method comprises the following steps: acquiring stress data of the stirring device at multiple moments, settable working parameter data of the stirring device and temperature data of a melt in the melting device; constructing a sample set, wherein each sample of the sample set comprises acquired stress data, working parameter data and temperature data of a melt of the stirring device at the same moment, the stress data and the working parameter data of the stirring device serve as auxiliary variables, the temperature data of the melt serve as a leading variable, and the sample set comprises a training sample set; training the measurement model through a training sample set; and acquiring current stress data and working parameter data of the stirring device in real time, and obtaining current temperature data of the melt in the melting device through the trained measurement model.
Description
Technical Field
The invention relates to the technical field of melting devices, in particular to a method and a system for measuring the temperature of a melt in a melting device.
Background
At present, in the nuclear industry field, the cold crucible glass solidification technology has the advantages of high treatment temperature, wide types of treatable wastes, long service life of a smelting furnace, easy retirement and the like, and becomes a more advanced technological means for radioactive waste treatment domestically and internationally. Due to the limited volume of the body of the cold crucible, when radioactive waste (i.e. radioactive waste liquid) mainly existing in a liquid state is treated, the radioactive waste liquid can be pretreated in advance by being provided with a calcining furnace (such as a rotary calcining furnace), the radioactive waste liquid is calcined and converted into a solid powder, and then the solid powder is introduced into the cold crucible for subsequent melting and solidification, and the method is called a two-step cold crucible glass solidification technology.
The main equipment of the two-step cold crucible glass solidification technology comprises a calcining furnace and a cold crucible. The cold crucible is used for generating high-frequency (105-106 Hz) current by using a power supply, and then the high-frequency current is converted into electromagnetic current by an induction coil to penetrate into a material to be treated, so that eddy current is formed to generate heat, and the material to be treated is directly heated and melted. The cold crucible mainly comprises a cold crucible body and a melting heating structure, wherein the cold crucible body is a container (the shape of the container is mainly circular or oval) formed by a metal arc-shaped block or a pipe which is communicated with cooling water, and the melting heating structure comprises an induction coil which is wound on the outer side of the cold crucible body and a high-frequency induction power supply which is electrically connected with the induction coil. After the material to be treated is placed in the cold crucible body, open the high frequency induction power and energize to induction coil, convert the electric current into electromagnetic current through induction coil and see through the wall body of the cold crucible body and get into inside the material to be treated to at the inside vortex production heat that forms of material to be treated, and then realize the heating of material to be treated. When the cold crucible works, cooling water is continuously introduced into the metal arc-shaped block or the pipe, the temperature of a melt in the body of the cold crucible is very high and can generally reach more than 2000 ℃, but the wall body of the cold crucible still keeps a lower temperature which is generally less than 200 ℃, so that a layer of solid (cold wall) with the thickness of 2-3 cm is formed in a low-temperature region of the melt close to the wall body of the cold crucible, and the cold crucible is called as a cold crucible.
When a cold crucible is used to process a material, the temperature of the melt in the cold crucible needs to be measured in order to analyze the melting process of the material, adjust the heating component of the cold crucible in real time, and the like.
In the prior art, the way of measuring the melt in the cold crucible is generally: temperature sensors (e.g., thermocouples) are inserted into the melt, and the temperature at various locations of the melt is measured by the temperature sensors. However, since the temperature of the melt is generally high, some melts may even be radioactive and/or corrosive, thereby affecting the service life of the temperature sensor. In order to ensure the normal operation of the cold crucible, the temperature sensor needs to be replaced frequently, which also increases the cost.
Disclosure of Invention
In view of the above, the present invention has been developed to provide a method and system for measuring the temperature of melt in a melting device that overcomes, or at least partially solves, the above-mentioned problems.
According to one aspect of the present invention, there is provided a method of measuring the temperature of a melt in a melting apparatus, the melt being continuously stirred by a stirring apparatus, the method comprising the steps of: acquiring stress data of the stirring device at multiple moments, settable working parameter data of the stirring device and temperature data of a melt in the melting device; constructing a sample set, wherein each sample of the sample set comprises acquired stress data, working parameter data and temperature data of a melt of the stirring device at the same moment, the stress data and the working parameter data of the stirring device serve as auxiliary variables, the temperature data of the melt serve as a leading variable, and the sample set comprises a training sample set; training the measurement model through a training sample set; and acquiring current stress data and working parameter data of the stirring device in real time, and obtaining current temperature data of the melt in the melting device through the trained measurement model.
Further, the measurement model is a measurement model established based on a neural network.
Further, the sample set further includes a verification sample set, and the step of training the measurement model by the training sample set further includes: and inputting the stress data and the working parameter data of the stirring device of each sample in the verification sample set into the trained measurement model and outputting a result, and comparing the output result with the temperature data of the melt of the corresponding sample in the verification sample set to verify the trained measurement model.
Further, the stress data of the stirring device comprises at least one of torque data, bending moment data and axial force data of the stirring device.
Further, the settable operating parameter of the stirring device comprises at least one of a position of the stirring device within the melting device in a lateral direction thereof, an angle at which the stirring device is disposed with respect to the melting device, a distance between the stirring device and a bottom wall of the melting device, and a rotational speed of the stirring device.
Further, the settable working parameter data of the stirring device is kept unchanged in each sample of the sample set, so as to train and obtain the measurement model under the specific working condition defined by the working parameter data of the stirring device.
Further, the temperature data of the melt within the melting device includes temperature data of the melt at a plurality of predetermined locations within the melting device.
Further, the plurality of preset positions are spaced apart in a transverse direction of the melting device, and/or the plurality of preset positions are spaced apart in a longitudinal direction of the melting device, and/or at least some of the plurality of preset positions are disposed near a bottom wall of the melting device.
According to another aspect of the present invention, there is also provided a system for measuring the temperature of a melt in a melting device, wherein the melting device is used for continuously stirring the melt in the melting device, and the system comprises a processor, and a temperature measuring device and a force measuring device which are in communication connection with the processor, wherein the processor is used for implementing the method for measuring the temperature of the melt in the melting device, the temperature measuring device is used for measuring the temperature data of the melt in the melting device in the stage of constructing a sample set, and the force measuring device is used for measuring the force data of the stirring device.
Further, the temperature measuring device may be selectively inserted into or removed from the melting device.
The measuring method comprises a measuring model determining stage and an actual temperature measuring stage. In the stage of determining the measurement model, the stress data of the stirring device, the settable working parameter data of the stirring device and the temperature data of the melt in the melting device corresponding to each moment are obtained aiming at a plurality of moments. Thereafter, a sample set is constructed using these data. Each sample of the sample set comprises stress data, working parameter data and temperature data of the melt of the stirring device at the same moment, wherein the stress data and the working parameter data of the stirring device are used as auxiliary variables, and the temperature data of the melt is used as a main variable. At least a part of the constructed samples in the sample set form a training sample set together, and the measurement model is trained through the training sample set to obtain the measurement model capable of reflecting the corresponding relation between the auxiliary variable (stress data and working parameter data of the stirring device) and the main variable (temperature data of the melt). And in the actual temperature measurement stage, acquiring the current stress data and the working parameter data of the stirring device in real time, and obtaining the current temperature data of the melt in the melting device through a measurement model obtained after training.
Because there is a certain relation between the temperature and viscosity of the melt in the melting device, the higher the temperature of the melt, the lower the viscosity of the melt, and the viscosity of the melt affects the stress condition of the stirring device which moves relative to the melt. At the same time, the settable operating parameters of the stirring device also influence the relationship between the temperature of the melt and the force applied to the stirring device. Therefore, the measuring method constructs a measuring model by selecting the stress data and the working parameter data of the stirring device as auxiliary variables and the temperature data of the melt as a main variable, and realizes the prediction of the temperature of the melt by using the stress and the working parameters of the stirring device which are easy to measure through the measuring model. The indirect measurement mode (also called as a soft measurement mode) can reflect the current temperature data of the melt without using a temperature sensor in the actual process, thereby overcoming the defects of short service life and frequent replacement of the temperature sensor, reducing the cost and ensuring that the temperature measurement is more accurate.
Drawings
Other objects and advantages of the present invention will become apparent from the following description of the invention which refers to the accompanying drawings, and may assist in a comprehensive understanding of the invention.
FIG. 1 is a schematic block diagram of a system for measuring the temperature of a melt in a melting apparatus according to one embodiment of the present invention;
FIG. 2 is a schematic view of the measuring system of FIG. 1 after varying the distance between the stirring device and the bottom wall of the melting device;
FIG. 3 is a block diagram of the measurement system of FIG. 1;
FIG. 4 is a schematic flow diagram of a method of measuring the temperature of the melt in the melting device according to one embodiment of the invention.
It is noted that the drawings are not necessarily to scale and are merely illustrative in nature and not intended to obscure the reader.
Description of reference numerals:
10. a melting device; 20. a melt; 30. a stirring device; 41. a processor; 42. a temperature measuring device; 43. a force measuring device; alpha, the setting angle of the stirring device relative to the melting device; h. the distance between the stirring device and the bottom wall of the melting device; v, the rotational speed of the stirring device.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention. It should be apparent that the described embodiment is one embodiment of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
It is to be noted that technical terms or scientific terms used herein should have the ordinary meaning as understood by those having ordinary skill in the art to which the present invention belongs, unless otherwise defined. If the description "first", "second", etc. is referred to throughout, the description of "first", "second", etc. is used only for distinguishing similar objects, and is not to be construed as indicating or implying a relative importance, order or number of technical features indicated, it being understood that the data described in "first", "second", etc. may be interchanged where appropriate. If "and/or" is presented throughout, it is meant to include three juxtapositions, exemplified by "A and/or B" and including either scheme A, or scheme B, or schemes in which both A and B are satisfied. Furthermore, spatially relative terms, such as "above," "below," "top," "bottom," and the like, may be used herein for ease of description to describe one element or feature's spatial relationship to another element or feature as illustrated in the figures, and should be understood to encompass different orientations in use or operation in addition to the orientation depicted in the figures.
The application provides a method and a system for measuring the temperature of a melt in a melting device. The melting device may be a melting device involved in a process flow in various fields, for example, the melting device may be a melting device (i.e., a cold crucible) used in a radioactive waste treatment process in the nuclear industry field, and the melting device is used for melting materials to be melted, such as a base material and a glass base material formed by radioactive waste (or after pretreatment).
FIG. 1 shows a schematic diagram of a system for measuring the temperature of a melt 20 in a melting apparatus 10 (e.g., a cold crucible) according to one embodiment. Fig. 2 shows a schematic illustration of the measuring system of fig. 1 after changing the distance between the stirring device 30 and the bottom wall of the melting device 10. Fig. 3 shows a block diagram of the measuring system of fig. 1. FIG. 4 shows a schematic flow diagram of one embodiment of a method for measuring the temperature of the melt 20 in the melting apparatus 10.
When adopting melting device to handle the material, generally can continue to stir through agitating unit to the melt in the melting device to guarantee the material misce bene, and reduce the temperature gradient that probably exists between each position of material, and then make the material fully react and obtain the product that the quality meets the requirements. Thus, in the embodiment of the measuring system shown in fig. 1 to 3, the melt 20 in the melting device 10 is continuously stirred by the stirring device 30.
As shown in fig. 4, in some embodiments of the present application, a method of measuring a temperature of a melt within a melting device includes the steps of:
step S10: acquiring stress data of the stirring device 30, settable working parameter data of the stirring device 30 and temperature data of the melt 20 in the melting device 10 at a plurality of moments;
step S20: constructing a sample set, wherein each sample of the sample set comprises acquired stress data and working parameter data of the stirring device 30 and temperature data of the melt 20 at the same moment, the stress data and the working parameter data of the stirring device 30 serve as auxiliary variables, the temperature data of the melt 20 serve as a main variable, and the sample set comprises a training sample set;
step S30: training the measurement model through a training sample set;
step S50: the current stress data and the working parameter data of the stirring device 30 are collected in real time, and the current temperature data of the melt 20 in the melting device 10 is obtained through the trained measurement model.
The measuring method comprises a measuring model determining stage and an actual temperature measuring stage.
The melting device, the stirring device and the related equipment used in the actual process are used as basic equipment for implementing the measuring method, and the environment constructed by the basic equipment is the actual use environment. Based on this, a measurement model determination stage of the above measurement method is performed. At this stage, the melt 20 in the melting device 10 may be a melt produced by actually performing a melting operation; alternatively, the medium may be a simulated medium capable of simulating an actual melt, for example, in the case of a melting apparatus for melting a base material and a glass base material formed by radioactive waste (or pretreated), the melt 20 may be a glass melt having a stable nuclide instead of a glass melt having a radionuclide generated in an actual process, and the glass melt having a stable nuclide is the simulated medium, so that the risk of radionuclide generation can be reduced while the characteristics of the actual melt are simulated as much as possible. And after the model to be measured is determined, directly carrying out an actual material melting process by using the equipment, and carrying out an actual temperature measuring stage of the measuring method.
In the measurement model determination phase, for a plurality of times, the stress data of the stirring device 30, the settable working parameter data of the stirring device 30 and the temperature data of the melt 20 in the melting device 10 corresponding to each time are acquired. Thereafter, a sample set is constructed using these data. Each sample of the sample set includes force data, working parameter data, and temperature data of the melt 20 of the stirring device 30 at the same time, where the force data and the working parameter data of the stirring device 30 are used as auxiliary variables, and the temperature data of the melt 20 is used as a main variable. At least a part of the samples in the constructed sample set jointly form a training sample set, and the measurement model is trained through the training sample set to obtain the measurement model capable of reflecting the corresponding relation between the auxiliary variable (the stress data and the working parameter data of the stirring device 30) and the main variable (the temperature data of the melt 20).
In the actual temperature measurement stage, the current stress data and the working parameter data of the stirring device 30 are collected in real time, and the current temperature data of the melt 20 in the melting device 10 is obtained through the measurement model obtained after training.
Because there is a correlation between the temperature and viscosity of the melt 20 in the melting device 10, the higher the temperature of the melt 20, the lower the viscosity thereof, and the viscosity of the melt 20 affects the stress of the stirring device 30 that moves relative thereto. At the same time, certain settable operating parameters of the stirring device 30 also influence the relationship between the temperature of the melt 20 and the force applied to the stirring device 30. The above-described measuring method therefore builds a measurement model by selecting the force data and the operating parameter data of the stirring device 30 as auxiliary variables and the temperature data of the melt 20 as main variables, by means of which it is achieved that the temperature of the melt 20 is predicted using the force and the operating parameters of the stirring device 30, which are easy to measure. By using the indirect measurement mode (also called as a soft measurement mode), the current temperature data of the melt 20 can be reflected without using a temperature sensor in the actual process, so that the defects of short service life and frequent replacement of the temperature sensor are overcome, the cost is reduced, and the temperature measurement is more accurate.
In the measurement model determination stage of the measurement method, there are various ways of establishing the measurement model. For example, the measurement model is a measurement model established based on a neural network. The neural network can be an LSTM neural network, a PB neural network or an RBF neural network. The method for establishing a soft measurement model based on a neural network is mature in the prior art, and is not described herein again. In addition, in other embodiments, the soft measurement model may be constructed by way of mathematical formulas based on relationships between force data (e.g., torque data) of the stirring device 30, operating parameter data, and temperature data of the melt 20.
As shown in fig. 4, in some embodiments of the present application, after step S30, the method further includes:
step S40: the sample set further includes a verification sample set, the stress data and the working parameter data of the stirring device 30 of each sample of the verification sample set are input to the trained measurement model and a result is output, and the output result is compared with the temperature data of the melt 20 of the corresponding sample in the verification sample set to verify the trained measurement model.
And verifying the trained measurement model through a verification sample set. Specifically, the force data and the operating parameter data of the stirring device 30 that verify one sample of the sample set are input to the trained measurement model as input values, the output result of the measurement model is the predicted value of the temperature data of the melt 20 corresponding to the input values, and the predicted value is compared with the temperature data of the melt 20 directly measured in the sample. The above process is performed for each sample in the verification sample set, thereby verifying the accuracy of the measurement model.
It should be noted that, in general, both the training sample set and the verification sample set need to include a plurality of samples. The number of samples in the training sample set may be greater than the number of samples in the validation sample set, e.g., the number of samples in the training sample set is more than three times the number of samples in the validation sample set. Theoretically, the more the number of samples in the training sample set is, the more accurate the obtained measurement model is. In the case that the number of samples in the training sample set is large enough, the number of samples in the verification sample set may be small, for example, the verification sample set includes one or two samples, or even the verification sample set may not be set.
In some embodiments of the present application, the force data of the stirring device 30 may include at least one of torque data, bending moment data, and axial force data of the stirring device 30. Preferably, the force data of the stirring device 30 includes torque data of the stirring device 30, and the torque data of the stirring device 30 is used as an auxiliary variable to indirectly reflect the temperature data of the melt 20 through the torque data of the stirring device 30. The torque data of the stirring device 30 is easy to measure, and the stirring body of the stirring device 30 is usually rotated along a fixed axis (for example, the central line of the stirring body is used as a rotating axis) during stirring, so that the torque data of the stirring device 30 is more closely related to the viscosity of the melt 20.
Further, the settable operating parameters of the stirring device 30 include at least one of a position of the stirring device 30 in a lateral direction thereof within the melting device 10, an arrangement angle α of the stirring device 30 with respect to the melting device 10, a distance h between the stirring device 30 and a bottom wall of the melting device 10, and a rotational speed v of the stirring device 30. As for what kind of settable working parameters of the stirring device 30 are selected as the auxiliary variables, the selection can be determined according to the conditions of the working parameters of the stirring device 30 in the actual process and the number of the auxiliary variables required to be input by the measurement model.
In some embodiments of the present application, the settable operating parameter data of the stirring device 30 is kept constant in each sample of the sample set to train to obtain a measurement model under the specific operating conditions of the stirring device 30 defined by the operating parameter data.
For example, in an actual process, the position of the stirring device 30 in the melting device 10 in the lateral direction thereof, the installation angle α with respect to the melting device 10, the distance h from the bottom wall of the melting device 10, and the rotational speed v are set in advance, and the above-mentioned operational parameters of the stirring device 30 are not changed during the melting operation of the melting device 10. At this time, at least one of the above-described operating parameters of the stirring device 30 is selected as an auxiliary variable. It should be noted that the term "auxiliary variable" means that the value can vary, and does not necessarily mean that the value of the data as the auxiliary variable is different in different samples. In the present embodiment, the force data of the stirring device 30 as the auxiliary variable varies with the temperature of the molten material 20 (i.e. the main variable), but the operating parameter of the stirring device 30 as the auxiliary variable does not vary, or the operating parameter of the stirring device 30 that does not vary defines a specific operating condition of the stirring device 30 (e.g. the angle α is α)1A distance h is h1V is a rotational speed v1). In theory, this should be allowed as long as it is possible to determine a measurement model that reflects the relationship between the force data of the stirring device 30 and the temperature data of the melt 20 in this particular operating condition. At this time, the trained measurement model is used to measure the temperature of the melt 20 of the melting device 10 when the stirring device 30 is under the above-mentioned specific condition.
Similarly, one of the operating parameters of the stirring device 30 may be adjusted according to various working conditions that the stirring device 30 may involve in the actual process, and after the adjustment, the operating parameter of the stirring device 30 remains unchanged (e.g., the distance h is adjusted to h)2The angle alpha is still kept as alpha1The rotational speed v is maintained at v1) Then the above-mentioned process is implemented, so that the training can obtain the specific working condition suitable for regulatedThe measurement model of (1). And in the same way, the data of at least one working parameter of the setting angle alpha of the stirring device 30 relative to the melting device 10, the distance h between the bottom wall of the melting device 10 and the rotating speed v are changed to define a specific working condition corresponding to the data, so that a measurement model corresponding to the specific working condition is obtained. When the melting device 10 actually performs the melting process, the current temperature data of the melt 20 in the melting device 10 can be obtained through the corresponding measurement model prediction by determining the working parameter data (used for reflecting the specific working condition) of the stirring device 30 and measuring the current stress data of the stirring device 30 in real time.
As shown in fig. 1 and 2, in some embodiments of the present application, the temperature data of the melt 20 within the melting device 10 includes temperature data of the melt 20 at a plurality of predetermined locations within the melting device 10. Preferably, the plurality of preset positions are spaced apart in a transverse direction of the melting device 10, and/or the plurality of preset positions are spaced apart in a longitudinal direction of the melting device 10, and/or at least some of the plurality of preset positions are located near a bottom wall of the melting device 10. The above-described manner enables prediction of temperature data of a plurality of locations of the melt 20 through current force data of the stirring device 30, thereby reflecting the current temperature distribution of the melt 20. Of course, in other embodiments, the temperature data for the melt 20 within the melting device 10 may include only the temperature data for the melt 20 at a particular location within the melting device 10.
As shown in fig. 1-3, in some embodiments of the present application, a system for measuring the temperature of melt within a melting device includes a processor 41 and a temperature measuring device 42 and a force measuring device 43 communicatively coupled to the processor 41. Wherein the processor 41 is used for implementing the above-mentioned measuring method, the temperature measuring device 42 is used for measuring the temperature data of the melt 20 in the melting device 10 in the stage of constructing the sample set, and the stress measuring device 43 is used for measuring the stress data of the stirring device 30. Preferably, the force data of the stirring device 30 comprises torque data of the stirring device 30, and the force measuring device 43 comprises a torque sensor for measuring the torque data of the stirring device 30. The temperature measuring device 42 includes a thermocouple. The torque data of the stirring device 30 is measured in real time by a torque sensor, and the temperature data of the melt 20 at a plurality of preset positions in the melting device 10 is measured in real time by a thermocouple, and the temperature data and the torque data form a corresponding relationship. In actual use, only the torque data of the stirring device 30 needs to be measured to reflect the current temperature data of the melt 20. In addition, in the present embodiment, the temperature measuring device 42 can be selectively inserted into the melting device 10 or removed from the melting device 10. When the measurement model determination phase is complete, the temperature measuring device 42 can be removed from the melting apparatus 10, thereby preventing the temperature measuring device 42 from being corroded by the melt 20 and affecting its life.
It should also be noted that, in the case of the embodiments of the present invention, features of the embodiments and examples may be combined with each other to obtain a new embodiment without conflict.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and the scope of the present invention is subject to the scope of the claims.
Claims (10)
1. A method for measuring the temperature of a melt in a melting device, characterized in that the melt (20) in the melting device (10) is continuously stirred by a stirring device (30), the method comprising the steps of:
acquiring stress data of the stirring device (30), settable working parameter data of the stirring device (30) and temperature data of the melt (20) in the melting device (10) at a plurality of moments;
constructing a sample set, wherein each sample of the sample set comprises stress data, working parameter data and temperature data of the melt (20) of the stirring device (30) at the same time, the stress data and the working parameter data of the stirring device (30) serve as auxiliary variables, the temperature data of the melt (20) serve as a main variable, and the sample set comprises a training sample set;
training a measurement model through the training sample set;
and acquiring the current stress data and the working parameter data of the stirring device (30) in real time, and obtaining the current temperature data of the melt (20) in the melting device (10) through the trained measurement model.
2. The method of claim 1,
the measurement model is established based on a neural network.
3. The method of claim 1,
the sample set further comprises a validation sample set, and the step of training the measurement model by the training sample set further comprises:
and inputting the stress data and the working parameter data of the stirring device (30) of each sample in the verification sample set into the trained measurement model and outputting a result, and comparing the output result with the temperature data of the melt (20) of the corresponding sample in the verification sample set to verify the trained measurement model.
4. The method according to any one of claims 1 to 3,
the stress data of the stirring device (30) comprises at least one of torque data, bending moment data and axial force data of the stirring device (30).
5. The method according to any one of claims 1 to 3,
the settable working parameter of the stirring device (30) comprises at least one of the position of the stirring device (30) in the melting device (10) along the transverse direction thereof, the setting angle of the stirring device (30) relative to the melting device (10), the distance between the stirring device (30) and the bottom wall of the melting device (10), and the rotating speed of the stirring device (30).
6. The method according to any one of claims 1 to 3,
in each sample of the sample set, the settable working parameter data of the stirring device (30) is kept unchanged, so as to train the measurement model under the specific working condition defined by the working parameter data of the stirring device (30).
7. The method according to any one of claims 1 to 3,
the temperature data of the melt (20) in the melting device (10) comprises temperature data of the melt (20) at a plurality of predetermined positions in the melting device (10).
8. The method of claim 7,
a plurality of said preset positions being arranged at intervals in a transverse direction of the melting device (10), and/or a plurality of said preset positions being arranged at intervals in a longitudinal direction of the melting device (10), and/or at least some of said preset positions being arranged close to a bottom wall of the melting device (10).
9. A system for measuring the temperature of melt in a melting device, characterized in that the melt (20) in the melting device (10) is continuously stirred by a stirring device (30), the system comprising a processor (41) and a temperature measuring device (42) and a force measuring device (43) which are communicatively connected to the processor (41),
wherein the processor (41) is configured to implement the method for measuring the temperature of a melt (20) in a melting device (10) according to any one of claims 1 to 8, the temperature measuring device (42) is configured to measure temperature data of the melt (20) in the melting device (10) during a set-up phase, and the force measuring device (43) is configured to measure force data of the stirring device (30).
10. The system of claim 9,
the temperature measuring device (42) can be selectively inserted into the melting device (10) or removed from the melting device (10).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110684262.4A CN113468684B (en) | 2021-06-21 | 2021-06-21 | Method and system for measuring temperature of melt in melting device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110684262.4A CN113468684B (en) | 2021-06-21 | 2021-06-21 | Method and system for measuring temperature of melt in melting device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113468684A true CN113468684A (en) | 2021-10-01 |
| CN113468684B CN113468684B (en) | 2022-07-01 |
Family
ID=77868779
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110684262.4A Active CN113468684B (en) | 2021-06-21 | 2021-06-21 | Method and system for measuring temperature of melt in melting device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113468684B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022268000A1 (en) * | 2021-06-21 | 2022-12-29 | 中国原子能科学研究院 | Temperature acquisition method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110322932A (en) * | 2019-07-11 | 2019-10-11 | 重庆科技学院 | Triazinone production process temperature of reaction kettle flexible measurement method and system |
| CN111695287A (en) * | 2020-04-22 | 2020-09-22 | 山东天岳先进材料科技有限公司 | Method and equipment for predicting overall temperature field in SiC single crystal furnace |
-
2021
- 2021-06-21 CN CN202110684262.4A patent/CN113468684B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110322932A (en) * | 2019-07-11 | 2019-10-11 | 重庆科技学院 | Triazinone production process temperature of reaction kettle flexible measurement method and system |
| CN111695287A (en) * | 2020-04-22 | 2020-09-22 | 山东天岳先进材料科技有限公司 | Method and equipment for predicting overall temperature field in SiC single crystal furnace |
Non-Patent Citations (1)
| Title |
|---|
| 郄东生 等: "机械搅拌对电磁冷坩埚熔化玻璃流场的影响", 《特种铸造及有色合金》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022268000A1 (en) * | 2021-06-21 | 2022-12-29 | 中国原子能科学研究院 | Temperature acquisition method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113468684B (en) | 2022-07-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101827671B (en) | The process of semiliquid metal and sensing apparatus and using method thereof | |
| FI57181B (en) | FASTRANSFORMATIONSMAETARE | |
| CN113468684B (en) | Method and system for measuring temperature of melt in melting device | |
| RU2499371C2 (en) | Method for determining emission measure for thermal emission, electric arc furnace, signal processing device, as well as programme code and information medium for implementation of method | |
| US7354491B2 (en) | Method and apparatus for universal metallurgical simulation and analysis | |
| CN104451037A (en) | Device and method for detecting temperature of RH refined liquid steel on line in real time | |
| JP6294566B2 (en) | System and method for determining the temperature of a metal melt in an electric arc furnace | |
| JP5683725B2 (en) | Method and control system for controlling melting and refining processes | |
| CN104391179A (en) | Conductivity test device and method for molten glass | |
| He et al. | A novel principle for molten steel level measurement in tundish by using temperature gradient | |
| US20150343530A1 (en) | Systems and methods for monitoring castings | |
| Meier et al. | Process modeling and simulation of the radiation in the electric arc furnace | |
| WO2020020478A1 (en) | Detection system, method for detecting of a melting condition of metal materials inside a furnace and for electromagnetic stirring, and furnace provided with such systems | |
| Zabadal et al. | Heat transfer process simulation by finite differences for online control of ladle furnaces | |
| CN101939656A (en) | Method and device for measuring the temperature of a hot spot in an oil-containing electric apparatus | |
| Kuo et al. | Prediction of heat-affected zone using Grey theory | |
| Umbrashko et al. | Experimental investigations and numerical modelling of the melting process in the cold crucible | |
| CN110057864B (en) | Simulation device and method for heating process of molten steel in water gap channel | |
| CN107576684A (en) | A kind of refractory material testing device for heat transferring performance and its application process | |
| WO2014024955A1 (en) | Casting quality management system and method | |
| Li et al. | Modeling of flow and temperature distribution in electroslag remelting withdrawal process for fabricating large-scale slab ingots | |
| JP4893930B2 (en) | Blackbody furnace | |
| Liu et al. | Inner wall temperature distribution measurement of the ladle based on cavity effective emissivity correction | |
| KR20170075242A (en) | Apparatus for predicting for shape of refractorie | |
| Roach et al. | Technical Development of New Concepts for Operation and Control of Cold Crucible Induction Melters for Vitrification of Radioactive Waste |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |