CN115106499B - Method and system for judging abnormal fluctuation of liquid level of crystallizer - Google Patents
Method and system for judging abnormal fluctuation of liquid level of crystallizer Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22D—CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES
- B22D11/00—Continuous casting of metals, i.e. casting in indefinite lengths
- B22D11/16—Controlling or regulating processes or operations
- B22D11/18—Controlling or regulating processes or operations for pouring
- B22D11/181—Controlling or regulating processes or operations for pouring responsive to molten metal level or slag level
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/141—Discrete Fourier transforms
- G06F17/142—Fast Fourier transforms, e.g. using a Cooley-Tukey type algorithm
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
- G06F17/148—Wavelet transforms
Abstract
The invention belongs to the technical field of continuous casting of metals, and particularly relates to a method and a system for judging abnormal fluctuation of a liquid level of a crystallizer, which can be applied to offline historical data analysis and online evaluation of fluctuation conditions of the liquid level of the crystallizer, reduce the influence of fluctuation of the liquid level of the crystallizer on the quality of a casting blank, reduce the quality loss of the casting blank and improve the continuous casting production benefit. By utilizing the fluctuation data of the liquid level of the crystallizer and based on an analysis method combining fast Fourier transformation and wavelet entropy, the fluctuation condition of molten steel in the crystallizer in a period of time (different furnace times or different casting times) can be comprehensively analyzed, the time for generating abnormal fluctuation of the liquid level can be accurately positioned, and the generation reason of the abnormal fluctuation of the liquid level can be rapidly traced.
Description
Technical Field
The invention relates to the technical field of metal continuous casting, in particular to a method and a system for judging abnormal fluctuation of a liquid level of a crystallizer.
Background
The mold is a core component of a continuous casting machine, one of the most important devices in the continuous casting process, called the heart of the continuous casting machine. The working condition of the casting machine directly affects the production efficiency and the casting blank quality of the continuous casting machine, so that a plurality of iron and steel enterprises at home and abroad pay great attention to research and develop and apply the high-efficiency crystallizer technology. The continuous casting process is generally an important step in limiting the steel yield, and a higher withdrawal speed is required to increase the continuous casting yield. It is known that during continuous casting, liquid steel enters the mold through a submerged nozzle and, due to the dispersion of the injection flow, waves are generated on the free surface of the mold. The fluctuation of the liquid level of the crystallizer not only affects the stability of continuous casting production, but also greatly affects the quality of casting blanks. The on-site continuous casting process pulling rate test shows that: as the withdrawal speed increases, the speed of molten steel injected into the crystallizer by the submerged nozzle increases, and as a result, the flow rate of molten steel flowing out of the submerged nozzle increases significantly, resulting in a sharp increase in the flow rate of molten steel in the crystallizer and meniscus turbulence, and as the fluctuation of the liquid level of the crystallizer increases, the content of nonmetallic inclusions in the skin of the cast blank increases significantly, thereby deteriorating the surface quality of the final product. Meanwhile, fluctuation of the liquid level can also bring slag rolling of the molten steel of the crystallizer, so that the content of inclusion in a casting blank exceeds the standard, and longitudinal cracking and steel leakage or slag inclusion of the casting blank can be caused when the content of inclusion is serious. Particularly in the ultra low carbon steel production process, casting blank defects caused by slag inclusion due to liquid level fluctuation become important factors affecting the quality of casting blanks.
It is currently generally accepted that liquid level fluctuations within a small range will not have a detrimental effect, and it is currently generally accepted that slab crystallizer liquid level fluctuations should be controlled within + -3 mm based on experience. Meanwhile, in order to track the quality of casting blanks and final products, more and more iron and steel enterprises begin to take fluctuation conditions of the liquid level of a crystallizer as key process control points for judging the quality of the casting blanks and the products. However, it is generally limited to marking the moment when the fluctuation of the mold level exceeds a certain range (for example, > + -3 mm or > + -5 mm), and to performing the marking inspection or degradation of the block or the furnace cast slab. In addition, there is a lack of means to further comprehensively evaluate the level of crystallizer level control, especially as large data analysis is stepped into the metallurgical field, and the vast amount of crystallizer level data is not effectively utilized. Therefore, aiming at the on-site crystallizer liquid level fluctuation and related data acquisition, the method is used for researching the abnormal crystallizer liquid level fluctuation and tracing the generation reason, and has important significance for obtaining good casting blank quality, improving continuous casting production efficiency and producing clean steel.
Disclosure of Invention
The invention provides a method and a system for judging abnormal fluctuation of a liquid level of a crystallizer, which can judge whether the liquid level of the crystallizer abnormally fluctuates and trace the generation reason of the abnormal fluctuation by utilizing the fluctuation data of the liquid level of the crystallizer.
In order to solve the technical problems, according to one aspect of the present invention, the following technical solutions are provided:
a method for judging abnormal fluctuation of a liquid level of a crystallizer comprises the following steps:
s1, analyzing crystallizer liquid level fluctuation data by adopting a fast Fourier transform analysis method to obtain information such as frequency and amplitude of the crystallizer liquid level fluctuation;
s2, accurately representing information such as frequency, amplitude and the like of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method;
s3, comparing the information of the accurate characterization with the historical information, and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
As a preferable scheme of the method for judging the abnormal fluctuation of the liquid level of the crystallizer, the method for judging the abnormal fluctuation of the liquid level of the crystallizer further comprises the following steps of,
s4, comparing the technological parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the technological parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes offline historical data and online collected data.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes an actual value of the crystallizer liquid level fluctuation, a set value of the crystallizer liquid level fluctuation, and the like.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S2, the fast fourier transform is as follows:
wherein x (lambda) is a spectral function; x (t) is the crystallizer surge signal; e, e -iλt Is a fourier transform kernel function; lambda is a frequency variable; t is a time variable.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S3, in the wavelet entropy analysis method, the expression of discrete wavelet transformation is:
in the formula, WT x (j, k) is a discrete wavelet transform of the original ripple signal x (t); x (t) is the crystallizer surge signal;is a wavelet basis function; j is the scale; k is time.
Set E 1 ，E 2 ，...，E j For the wavelet energy spectrum of signal x (t) on the j scale, E is then on the scale domain j A division of the signal energy may be formed; after the signal x (t) is subjected to wavelet decomposition, the wavelet coefficient energy sum under the j scale is as follows:
wherein N-is the number of wavelet coefficients under the scale of j;
D j (k) Is a set of wavelet coefficients at the j scale.
From the characteristics of wavelet transformation, E is the power of each component E j Sum p j ＝E j E, then sigma j p j =1, thus defining wavelet entropy W EE The method comprises the following steps:
W EE ＝-∑ j p j log(pj) (4)
according to the invention, the original fluctuation signal is decomposed by using the formula (1), the information such as the frequency, the amplitude and the like corresponding to the fluctuation of the liquid level of the crystallizer are determined, the time and the scale are refined by wavelet entropy analysis in combination with the formulas (2) - (4), the conversion relation of the frequency and the amplitude in the formula (1) is accurately represented, and whether the fluctuation of the liquid level of the crystallizer is abnormal or not can be rapidly judged.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S3, the history information includes history normal information and history abnormal information.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S4, the process parameters include process parameters and equipment parameters, the process parameters include a casting blank pulling speed, a stopper rod position, a water gap nodulation size, a casting blank bulging parameter, and the like, and the equipment parameters include a continuous casting machine setting parameter and the like.
In order to solve the above technical problems, according to another aspect of the present invention, the following technical solutions are provided:
a crystallizer liquid level abnormal fluctuation discrimination system comprises:
the data processing module is used for analyzing the fluctuation data of the liquid level of the crystallizer based on a fast Fourier transform analysis method to obtain information such as the frequency, the amplitude and the like of the fluctuation of the liquid level of the crystallizer;
the accurate characterization module is used for accurately characterizing the information such as the frequency, the amplitude and the like of the liquid level fluctuation of the crystallizer based on a wavelet entropy analysis method;
and the abnormal fluctuation judging module is used for comparing the accurately-represented information with the historical information and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging system, the system further comprises:
the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
In order to solve the above technical problems, according to another aspect of the present invention, the following technical solutions are provided:
an information data processing terminal for realizing the crystallizer liquid level abnormal fluctuation judging method.
A computer-readable storage medium comprising instructions that, when run on a computer, cause the computer to perform the above-described crystallizer level abnormality fluctuation discrimination method.
The beneficial effects of the invention are as follows:
the invention provides a method and a system for judging abnormal fluctuation of the liquid level of a crystallizer, which utilize the fluctuation data of the liquid level of the crystallizer, are based on an analysis method combining fast Fourier transformation and wavelet entropy, and can comprehensively analyze the fluctuation condition of molten steel in the crystallizer within a period of time (different furnace times or different casting times), accurately position the time for generating abnormal fluctuation of the liquid level and quickly trace the cause of the abnormal fluctuation of the liquid level; the method can be applied to offline historical data analysis and online evaluation of the fluctuation condition of the liquid level of the crystallizer, reduces the influence of the fluctuation of the liquid level of the crystallizer on the quality of the casting blank, reduces the quality loss of the casting blank and improves the continuous casting production benefit.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a discriminating method of the present invention;
FIG. 2 is a schematic diagram of a discriminating apparatus according to the present invention;
FIG. 3 is a graph showing the information of the normal fluctuation of the liquid level of the crystallizer in the embodiment 1 of the invention;
FIG. 4 is a graph showing abnormal fluctuation information of the liquid level of the crystallizer in example 1 of the present invention;
FIG. 5 is a graph showing the information of the normal fluctuation of the liquid level of the crystallizer in the embodiment 2 of the present invention;
FIG. 6 is a graph showing abnormal fluctuation information of the liquid level of the crystallizer in example 2 of the present invention;
FIG. 7 is a graph showing the information of the normal fluctuation of the liquid level of the crystallizer in example 3 of the present invention;
FIG. 8 is a graph showing information of abnormal fluctuation of the mold level in example 3 of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description will be made clearly and fully with reference to the technical solutions in the embodiments, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a method and a system for judging abnormal fluctuation of a liquid level of a crystallizer, which can be applied to offline historical data analysis and online evaluation of fluctuation conditions of the liquid level of the crystallizer, reduce the influence of fluctuation of the liquid level of the crystallizer on the quality of a casting blank, reduce the quality loss of the casting blank and improve the continuous casting production benefit. By utilizing the fluctuation data of the liquid level of the crystallizer and based on an analysis method combining fast Fourier transformation and wavelet entropy, the fluctuation condition of molten steel in the crystallizer in a period of time (different furnace times or different casting times) can be comprehensively analyzed, the time for generating abnormal fluctuation of the liquid level can be accurately positioned, and the generation reason of the abnormal fluctuation of the liquid level can be rapidly traced.
According to one aspect of the invention, the invention provides the following technical scheme:
a method for judging abnormal fluctuation of a liquid level of a crystallizer comprises the following steps:
s1, analyzing crystallizer liquid level fluctuation data by adopting a fast Fourier transform analysis method to obtain information such as frequency and amplitude of the crystallizer liquid level fluctuation;
s2, accurately representing information such as frequency, amplitude and the like of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method;
s3, comparing the information of the accurate characterization with the historical information, and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
The method for judging abnormal fluctuation of the liquid level of the crystallizer further comprises the steps of,
s4, comparing the technological parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the technological parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
Providing sufficient field data by utilizing a field complete data acquisition system, providing a crystallizer liquid level fluctuation analysis method, inputting the data such as an actual value, a set value and the like of the crystallizer liquid level fluctuation acquired by utilizing the system into the crystallizer liquid level fluctuation analysis method based on fast Fourier transform and wavelet entropy calculation, extracting the frequency and the amplitude corresponding to the liquid level fluctuation generated in the casting process by utilizing the fast Fourier transform, accurately characterizing the information such as the fluctuation frequency and the amplitude by utilizing the wavelet entropy, and comparing the information accurately characterized with historical information, thereby rapidly judging whether the liquid level fluctuation is abnormal or not, and determining the cause of the abnormal fluctuation by analyzing the change of process parameters corresponding to the normal and abnormal fluctuation.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes offline historical data and online collected data, so that the method can be applied to offline historical data analysis and online evaluation of the crystallizer liquid level fluctuation condition, reduce the influence of the crystallizer liquid level fluctuation on the quality of a casting blank, reduce the quality loss of the casting blank and improve the continuous casting production benefit.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes an actual value of the crystallizer liquid level fluctuation, a set value of the crystallizer liquid level fluctuation, and the like.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S2, the fast fourier transform is as follows:
wherein x (lambda) is a spectral function; x (t) is the crystallizer surge signal; e, e -iλt Is a fourier transform kernel function; lambda is a frequency variable; t is a time variable.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S3, the technical solution of the present invention may be implemented by using a wavelet entropy analysis method commonly used in the prior art, and the following description will be given by taking a wavelet entropy analysis method commonly used in the art as an example, where the expression of discrete wavelet transformation in the wavelet entropy analysis method is:
in the formula, WT x (j, k) is a discrete wavelet transform of the original ripple signal x (t); x (t) is the crystallizer surge signal;is a wavelet basis function; j is the scale; k is time.
Set E 1 ，E 2 ，...，E j For the wavelet energy spectrum of signal x (t) on the j scale, E is then on the scale domain j A division of the signal energy may be formed; after the signal x (t) is subjected to wavelet decomposition, the wavelet coefficient energy sum under the j scale is as follows:
wherein N-is the number of wavelet coefficients under the scale of j;
D j (k) Is a set of wavelet coefficients at the j scale.
From the characteristics of wavelet transformation, E is the power of each component E j Sum ofAnd p is j ＝E j E, then sigma j p j =1, thus defining wavelet entropy W EE The method comprises the following steps:
W EE ＝-∑ j p j log(pj) (4)
according to the invention, the original fluctuation signal is decomposed by using the formula (1), the information such as the frequency, the amplitude and the like corresponding to the fluctuation of the liquid level of the crystallizer are determined, the time and the scale are refined by wavelet entropy analysis in combination with the formulas (2) - (4), the conversion relation of the frequency and the amplitude in the formula (1) is accurately represented, and whether the fluctuation of the liquid level of the crystallizer is abnormal or not can be rapidly judged.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S3, the history information includes history normal information and history abnormal information.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging method, the invention comprises the following steps: in the step S4, the process parameters include, but are not limited to, process parameters including, but not limited to, a casting speed, a stopper rod position, a nozzle nodulation size, a casting bloom parameter, and the like, and equipment parameters including, but not limited to, a continuous casting machine setting parameter, and the like.
A crystallizer liquid level abnormal fluctuation discrimination system comprises:
the data processing module is used for analyzing the fluctuation data of the liquid level of the crystallizer based on a fast Fourier transform analysis method to obtain information such as the frequency, the amplitude and the like of the fluctuation of the liquid level of the crystallizer;
the accurate characterization module is used for accurately characterizing the information such as the frequency, the amplitude and the like of the liquid level fluctuation of the crystallizer based on a wavelet entropy analysis method;
and the abnormal fluctuation judging module is used for comparing the accurately-represented information with the historical information and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
As a preferable scheme of the crystallizer liquid level abnormal fluctuation judging system, the system further comprises:
the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
According to another aspect of the invention, the invention provides the following technical scheme:
an information data processing terminal for realizing the crystallizer liquid level abnormal fluctuation judging method.
A computer-readable storage medium comprising instructions that, when run on a computer, cause the computer to perform the above-described crystallizer level abnormality fluctuation discrimination method.
The invention can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When used in whole or in part, is implemented in the form of a computer program product comprising one or more computer instructions. When loaded or executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
Example 1
The embodiment is used for the continuous casting production process of the plate blank (the section size of the casting blank is 1500mm multiplied by 220 mm), and comprises the following steps:
on the premise of stable casting on site, the fluctuation of the liquid level of the crystallizer and relevant technological parameters thereof in a period of time are collected at a certain collection frequency;
based on an analysis method combining fast Fourier transform and wavelet entropy, the liquid level fluctuation data of the crystallizer is analyzed, the fast Fourier transform is applied to extract frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods, the wavelet entropy is utilized to combine information such as frequency and the like to make unified characterization, and the unified characterization is compared with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that the liquid level fluctuation of the crystallizer is accurately judged.
As shown in FIG. 3, the fluctuation frequency mainly exists in a 0-1 Hz area, the amplitude of the frequency band is smaller than 0.2 in a 0-0.4 Hz area, the amplitude of the frequency band in a 0.4-0.8 Hz area is smaller than 0.1, the wave frequency is characterized by wavelet entropy, the wavelet entropy in a 0-0.4 Hz frequency range is 0.0136, the wavelet entropy in a 0.4-0.8 Hz frequency range is 0.0061, and the wavelet entropy value of the frequency range is positioned in the normal fluctuation range of the liquid level.
As shown in FIG. 4, the fluctuation frequency mainly exists in a 0-1 Hz area, the amplitude of the frequency in the 0-0.4 Hz area and the amplitude of the frequency in the 0.4-0.8 Hz area are not greatly different, the amplitude of the two frequency ranges are smaller than 0.35, the wavelet entropy is used for characterization, the wavelet entropy is 0.0971 in the 0-0.4 Hz frequency range, the wavelet entropy is 0.0963 in the 0.4-0.8 Hz frequency range, and the wavelet entropy value of the frequency range is positioned in the abnormal fluctuation range of the liquid level.
In combination with the process parameters corresponding to the positive and abnormal fluctuation of the liquid level of the crystallizer in fig. 3 and 4, it is clear that the reason for the abnormal fluctuation of the liquid level of the crystallizer in the embodiment is that the position of the stopper rod rises by about 3mm, which indicates that the immersed nozzle has a certain degree of nodulation, and the fluctuation of the position of the stopper rod in the abnormal section is more serious than that in the normal section, and part of the nodulation water gap possibly falls off, thereby influencing the fluctuation of the liquid level of the crystallizer.
Example 2
The embodiment is used for the continuous casting production process of the plate blank (the section size of the casting blank is 1500mm multiplied by 220 mm), and comprises the following steps:
on the premise of stable casting on site, the fluctuation of the liquid level of the crystallizer and relevant technological parameters thereof in a period of time are collected at a certain collection frequency;
based on an analysis method combining fast Fourier transform and wavelet entropy, the liquid level fluctuation data of the crystallizer is analyzed, the fast Fourier transform is applied to extract frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods, the wavelet entropy is utilized to combine information such as frequency and the like to make unified characterization, and the unified characterization is compared with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that the liquid level fluctuation of the crystallizer is accurately judged.
As shown in FIG. 5, the fluctuation frequency mainly exists in a 0-1 Hz area, the amplitude of the frequency band is smaller than 0.2 in a 0-0.4 Hz area, the amplitude of the frequency band in a 0.4-0.8 Hz area is smaller than 0.1, the wave frequency is characterized by wavelet entropy, the wavelet entropy in a 0-0.4 Hz frequency range is 0.0179, the wavelet entropy in a 0.4-0.8 Hz frequency range is 0.0071, and the wavelet entropy value of the frequency range is positioned in the normal fluctuation range of the liquid level.
As shown in FIG. 6, the fluctuation frequency mainly exists in a 0-1 Hz area, the amplitude of the frequency in the 0-0.4 Hz area and the amplitude of the frequency in the 0.4-0.8 Hz area are not greatly different, the amplitude of the two frequency ranges are smaller than 0.4, the wavelet entropy is used for characterization, the wavelet entropy is 0.1007 in the 0-0.4 Hz frequency range, the wavelet entropy is 0.1200 in the 0.4-0.8 Hz frequency range, and the wavelet entropy value of the frequency range is positioned in the abnormal fluctuation range of the liquid level.
In combination with the process parameters corresponding to the positive and abnormal fluctuation of the liquid level of the crystallizer in fig. 5 and 6, it is clear that the reason for the abnormal fluctuation of the liquid level of the crystallizer in the embodiment is that the temperature of the tundish is reduced by about 15 ℃, at this time, the temperature interval of the tundish is at the lower limit of the superheat degree, and may even be lower than the specified superheat degree, the fluidity of the molten steel is poor, the floating removal of the inclusions is affected, the nodulation rate of the water gap is accelerated, and the position change of the stopper rod is aggravated, so that the abnormal fluctuation of the liquid level of the crystallizer is generated.
Example 3
The embodiment is based on the continuous casting production process of slab by a slab crystallizer (the section size of a casting blank is 1200mm multiplied by 230 mm) with an electromagnetic braking device in a certain factory, and comprises the following steps:
on the premise of stable casting on site, the fluctuation of the liquid level of the crystallizer and relevant technological parameters thereof in a period of time are collected at a certain collection frequency;
based on an analysis method combining fast Fourier transform and wavelet entropy, the liquid level fluctuation data of the crystallizer is analyzed, the fast Fourier transform is applied to extract frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods, the wavelet entropy is utilized to combine information such as frequency and the like to make unified characterization, and the unified characterization is compared with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that the liquid level fluctuation of the crystallizer is accurately judged.
As shown in FIG. 7, the fluctuation frequency mainly exists in a 0-1 Hz area, the amplitude of the frequency band is smaller than 0.25 in a 0-0.4 Hz area, the amplitude of the frequency band in a 0.4-0.8 Hz area is smaller than 0.15, the wave frequency is characterized by wavelet entropy, the wavelet entropy in a 0-0.4 Hz frequency range is 0.0507, the wavelet entropy in a 0.4-0.8 Hz frequency range is 0.0143, and the wavelet entropy value of the frequency range is positioned in the normal fluctuation range of the liquid level.
As shown in FIG. 8, the fluctuation frequency mainly exists in a 0-1.5 Hz area, the frequency is concentrated in a 0-0.4 Hz area, the amplitude of the frequency range is smaller than that of the 1,0.4-0.8 Hz area, the amplitude of the frequency is smaller than that of the frequency 3, the wavelet entropy is used for characterization, the wavelet entropy is 0.1912 in the 0-0.4 Hz frequency range, the wavelet entropy is 0.0360 in the 0.4-0.8 Hz frequency range, and the wavelet entropy value of the frequency range is located in the abnormal fluctuation range of the liquid level.
In combination with the process parameters corresponding to the positive and abnormal fluctuation of the liquid level of the crystallizer in fig. 7 and 8, it is clear that the reason for the abnormal fluctuation of the liquid level of the crystallizer in the embodiment is that the pulling speed is increased by 0.2m/min, and after the pulling speed is increased from 1.4m/min to 1.6m/min, the amplitude of the frequency region of 0-0.4 Hz and the corresponding wavelet entropy value are greatly increased, so that the abnormal fluctuation of the crystallizer is caused.
The analysis method combining the fast Fourier transform and the wavelet entropy can be intuitively embodied by the 3 embodiments, so that the normal fluctuation and the abnormal fluctuation of the liquid level of the crystallizer can be accurately judged, the feasibility of the judgment method is proved, the quality of a casting blank in the continuous casting production process can be further judged, and on the basis of different types of crystallizers, the method can be adopted, according to the judgment result, relevant technological parameters corresponding to the normal fluctuation and the abnormal fluctuation are analyzed and compared, the reason for the abnormal fluctuation is searched, and the abnormal fluctuation of the crystallizer can be effectively controlled, so that the quality of the casting blank and the continuous casting production efficiency are improved.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structural changes made by the content of the present invention or direct/indirect application in other related technical fields are included in the scope of the present invention.
Claims (8)
1. The method for judging abnormal fluctuation of the liquid level of the crystallizer is characterized by comprising the following steps of:
s1, analyzing the fluctuation data of the liquid level of the crystallizer by adopting a fast Fourier transform analysis method to obtain the frequency and amplitude information of the fluctuation of the liquid level of the crystallizer; the fast fourier transform is:
wherein x (lambda) is a spectral function; x (t) is the crystallizer surge signal; e, e -iλt Is a fourier transform kernel function; lambda is a frequency variable; t is a time variable;
s2, accurately representing the frequency and amplitude information of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method; in the wavelet entropy analysis method, the expression of discrete wavelet transformation is as follows:
in the formula, WT x (j, k) is a discrete wavelet transform of the original ripple signal x (t); x (t) is the crystallizer surge signal;is a wavelet basis function; j is the scale; k is time;
set E 1 ,E 2 ,…,E j For the wavelet energy spectrum of signal x (t) on the j scale, E is then on the scale domain j A division of the signal energy may be formed; after the signal x (t) is subjected to wavelet decomposition, the wavelet coefficient energy sum under the j scale is as follows:
wherein N-is the number of wavelet coefficients under the scale of j;
D j (k) A set of wavelet coefficients at the j scale;
from the characteristics of wavelet transformation, E is the power of each component E j Sum p j ＝E j E, then sigma j p j =1, thus defining wavelet entropy W EE The method comprises the following steps:
W EE ＝-∑ j p j log(p j ) (4)；
s3, comparing the information of the accurate characterization with the historical information, and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
2. The method for judging abnormal fluctuation of a mold liquid level according to claim 1, further comprising,
s4, comparing the technological parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the technological parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
3. The method according to claim 1 or 2, wherein in the step S1, the crystallizer liquid level fluctuation data includes offline historical data and online collected data.
4. The method according to claim 2, wherein in the step S4, the process parameters include a casting speed, a stopper position, a nozzle nodulation size, a casting bulging parameter, and a continuous casting machine setting parameter.
5. A crystallizer liquid level abnormality fluctuation discrimination system for realizing the crystallizer liquid level abnormality fluctuation discrimination method according to any one of claims 1 to 4, comprising:
the data processing module is used for analyzing the fluctuation data of the liquid level of the crystallizer based on a fast Fourier transform analysis method to obtain the frequency and amplitude information of the fluctuation of the liquid level of the crystallizer;
the accurate characterization module is used for accurately characterizing the frequency and amplitude information of the liquid level fluctuation of the crystallizer based on a wavelet entropy analysis method;
and the abnormal fluctuation judging module is used for comparing the accurately-represented information with the historical information and judging whether the fluctuation of the liquid level of the crystallizer is abnormal or not.
6. The crystallizer liquid level abnormality and fluctuation discrimination system according to claim 5, further comprising:
the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy values of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy values of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason for the abnormal fluctuation of the liquid level of the crystallizer.
7. An information data processing terminal for realizing the method for discriminating abnormal fluctuation of a mold liquid level according to any one of claims 1 to 4.
8. A computer readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the crystallizer liquid level abnormality wave discrimination method of any one of claims 1 to 4.
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