CN115106499A - Crystallizer liquid level abnormal fluctuation distinguishing method and system - Google Patents
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Abstract
The invention belongs to the technical field of metal continuous casting, and particularly relates to a method and a system for judging the abnormal fluctuation of a crystallizer liquid level, which can be applied to off-line historical data analysis and on-line evaluation of the fluctuation condition of the crystallizer liquid level, reduce the influence of the fluctuation of the crystallizer liquid level 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 crystallizer liquid level fluctuation data and based on an analysis method combining fast Fourier transform and wavelet entropy, the fluctuation condition of the molten steel in the crystallizer within a period of time (different furnaces or different casting times) can be comprehensively analyzed, the time of the liquid level abnormal fluctuation can be accurately positioned, and the reason of the liquid level abnormal fluctuation can be quickly 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 the abnormal fluctuation of a crystallizer liquid level.
Background
The crystallizer is a core component of a continuous casting machine, is one of the most important devices in the continuous casting process, and is called the heart of the continuous casting machine. The working condition of the crystallizer directly influences the production efficiency of a continuous casting machine and the quality of casting blanks, so that a plurality of iron and steel enterprises at home and abroad pay great attention to research, development and application of efficient crystallizer technology. The continuous casting process is usually an important link for limiting the steel yield, and a higher withdrawal speed is required to improve the continuous casting yield. It is known that during continuous casting, liquid steel enters the mould through a submerged entry nozzle, generating undulations on the free surface of the mould due to the dispersion of the flow. The fluctuation of the liquid level of the crystallizer not only influences the stability of continuous casting production, but also has great influence on the quality of casting blanks. The pulling speed test in the field continuous casting process shows that: along with the increase of the casting speed, the speed of the submerged nozzle for injecting molten steel into the crystallizer is increased, and as a result, the flow speed of the molten steel flowing out of the submerged nozzle is obviously increased, so that the flow speed of the molten steel in the crystallizer and the turbulence of a meniscus are sharply increased, and along with the aggravation of the fluctuation of the liquid level of the crystallizer, the content of nonmetallic inclusions under a casting blank is obviously increased, and further the surface quality of a final product is deteriorated. Meanwhile, the fluctuation of the liquid level can bring slag entrapment of the molten steel of the crystallizer, the content of impurities in the casting blank exceeds the standard, and the casting blank is longitudinally cracked and leaked or slag is included in serious conditions. Particularly, in the production process of ultra-low carbon steel, casting slab defects caused by slag entrapment due to fluctuation of liquid level have become important factors affecting the quality of casting slabs.
At present, the liquid level fluctuation in a small range is generally considered not to generate harmful influence, and the liquid level fluctuation of the slab crystallizer is generally considered to be controlled within +/-3 mm according to experience at present. Meanwhile, in order to track the quality of the casting blank and the final product, more and more steel enterprises begin to use the fluctuation condition of the crystallizer liquid level as a key process control point for judging the quality of the casting blank and the product. However, currently, it is generally limited to mark the moment when the level fluctuation of the mold exceeds a certain range (for example, > +/-3 mm or > +/-5 mm), and to mark the block or the cast ingot for inspection or degradation. In addition, means for further and comprehensively evaluating the control level of the crystallizer liquid level is lacked, and especially when big data analysis gradually enters the metallurgical field, massive crystallizer liquid level data are lacked to be effectively utilized. Therefore, aiming at on-site crystallizer liquid level fluctuation and related data acquisition, the method researches the abnormal fluctuation of the crystallizer liquid level and traces the reasons for the abnormal fluctuation, 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 the abnormal fluctuation of a crystallizer liquid level, which can judge whether the liquid level of the crystallizer fluctuates abnormally or not and trace the reason of the abnormal fluctuation by utilizing the fluctuation data of the liquid level of the crystallizer.
To solve the above technical problem, according to an aspect of the present invention, the present invention provides the following technical solutions:
a method for judging the abnormal fluctuation of the 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, amplitude and the like of crystallizer liquid level fluctuation;
s2, accurately representing information such as frequency and amplitude of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method;
and S3, comparing the accurately characterized information with historical information, and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
As a preferable embodiment of the method for determining the abnormal fluctuation of the liquid level of the crystallizer according to the present invention, the method for determining the abnormal fluctuation of the liquid level of the crystallizer further comprises,
s4, comparing the process parameters corresponding to the wavelet entropy of the crystallizer liquid level abnormal fluctuation with the process parameters corresponding to the wavelet entropy of the crystallizer liquid level normal fluctuation, and finding out the reason causing the crystallizer liquid level abnormal fluctuation.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method 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 method for judging the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes a crystallizer liquid level fluctuation actual value, a crystallizer liquid level fluctuation set value, and the like.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S2, the fast fourier transform is:
wherein x (λ) is a spectral function; x (t) is a crystallizer fluctuation signal; e.g. of the type -iλt Is a Fourier transform kernel function; λ is a frequency variable; t is a time variable.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S3, in the wavelet entropy analysis method, the discrete wavelet transform expression is:
in the formula, WT x (j, k) is a discrete wavelet transform for the original undulation signal x (t); x (t) is a crystallizer fluctuation signal;
is a wavelet basis function; j is the scale; k is time.
Let E 1 ，E 2 ，...，E j For the wavelet spectrum of the signal x (t) on the j scale, E is on the scale domain j A division of the signal energy may be formed; after wavelet decomposition, the sum of wavelet coefficient energies at j scale of signal x (t) is:
in the formula, N is the number of wavelet coefficients under the j scale;
D j (k) is a set of wavelet coefficients at the j-scale.
According to the characteristics of wavelet transformation, E is the power E of each component j And p is j ＝E j E, then ∑ j p j 1, therefore, a wavelet entropy W is defined EE Comprises the following steps:
W EE ＝-∑ j p j log(pj) (4)
the method utilizes the formula (1) to decompose the original fluctuation signal, determines the information such as frequency, amplitude and the like corresponding to the crystallizer liquid level fluctuation, combines the formulas (2) to (4), refines time and scale through wavelet entropy analysis, accurately represents the transformation relation of the frequency and the amplitude in the formula (1), and can quickly judge whether the crystallizer liquid level fluctuation is abnormal or not.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S3, the history information includes history normal information and history abnormal information.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in the step S4, the process parameters include process parameters and equipment parameters, the process parameters include casting blank pulling speed, stopper rod position, nozzle nodule size, casting blank bulging parameters, and the like, and the equipment parameters include continuous casting machine setting parameters, and the like.
In order to solve the above technical problem, according to another aspect of the present invention, the present invention provides the following technical solutions:
a crystallizer liquid level abnormal fluctuation distinguishing system comprises:
the data processing module is used for analyzing the crystallizer liquid level fluctuation data based on a fast Fourier transform analysis method to obtain information such as frequency, amplitude and the like of the crystallizer liquid level fluctuation;
the precise representation module is used for accurately representing information such as frequency, 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 historical information and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
As a preferable embodiment of the system for judging the abnormal fluctuation of the liquid level of the crystallizer according to the present invention, the system further includes:
and the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy value of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy value of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason causing the abnormal fluctuation of the liquid level of the crystallizer.
In order to solve the above technical problem, according to another aspect of the present invention, the present invention provides the following technical solutions:
an information data processing terminal for realizing the crystallizer liquid level abnormal fluctuation distinguishing method.
A computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to execute the above-described crystallizer liquid level abnormal fluctuation discrimination method.
The invention has the following beneficial effects:
the invention provides a method and a system for judging the abnormal fluctuation of a liquid level of a crystallizer, which utilize the fluctuation data of the liquid level of the crystallizer and an analysis method based on the combination of fast Fourier transform and wavelet entropy, can comprehensively analyze the fluctuation condition of molten steel in the crystallizer within a period of time (different heats or different casting times), accurately position the time generated by the abnormal fluctuation of the liquid level and quickly trace the reason generated by the abnormal fluctuation of the liquid level; the method can be applied to off-line historical data analysis, can also be applied to on-line 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 production benefit of continuous casting.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of a determination method according to the present invention;
FIG. 2 is a schematic view of a discriminating apparatus according to the present invention;
FIG. 3 is a diagram showing information on normal fluctuation of the liquid level of the crystallizer in example 1 of the present invention;
FIG. 4 is a diagram showing information about the abnormal fluctuation of the liquid level in the crystallizer in accordance with embodiment 1 of the present invention;
FIG. 5 is a diagram showing information on the normal fluctuation of the liquid level in the crystallizer in example 2 of the present invention;
FIG. 6 is a diagram showing information on the abnormal fluctuation of the liquid level in the crystallizer in example 2 of the present invention;
FIG. 7 is a diagram showing information on the normal fluctuation of the crystallizer liquid level in example 3 of the present invention;
FIG. 8 is a diagram showing information on the abnormal fluctuation of the mold liquid level in example 3 of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The following will clearly and completely describe the technical solutions in the embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method and a system for judging the abnormal fluctuation of a crystallizer liquid level, which can be applied to off-line historical data analysis and on-line evaluation of the fluctuation condition of the crystallizer liquid level, reduce the influence of the fluctuation of the crystallizer liquid level on the quality of a casting blank, reduce the quality loss of the casting blank and improve the production benefit of continuous casting. By utilizing the crystallizer liquid level fluctuation data and based on an analysis method combining fast Fourier transform and wavelet entropy, the fluctuation condition of the molten steel in the crystallizer within a period of time (different furnaces or different casting times) can be comprehensively analyzed, the time of the liquid level abnormal fluctuation can be accurately positioned, and the reason of the liquid level abnormal fluctuation can be quickly traced.
According to one aspect of the invention, the invention provides the following technical scheme:
a method for judging the abnormal fluctuation of the 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, amplitude and the like of crystallizer liquid level fluctuation;
s2, accurately representing information such as frequency and amplitude of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method;
and S3, comparing the accurately characterized information with historical information, and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
The method for judging the abnormal fluctuation of the liquid level of the crystallizer further comprises the following steps,
s4, comparing the process parameters corresponding to the wavelet entropy of the crystallizer liquid level abnormal fluctuation with the process parameters corresponding to the wavelet entropy of the crystallizer liquid level normal fluctuation, and finding out the reason causing the crystallizer liquid level abnormal fluctuation.
The method comprises the steps of providing sufficient field data by using a field complete data acquisition system, providing a crystallizer liquid level fluctuation analysis method, inputting data such as crystallizer liquid level fluctuation actual values and set values acquired by the system into a crystallizer liquid level fluctuation analysis method based on fast Fourier transform and wavelet entropy calculation, extracting frequencies and amplitudes corresponding to liquid level fluctuation generated in the casting process by using the fast Fourier transform, accurately representing information such as fluctuation frequencies and amplitudes by using the wavelet entropy, comparing the information of the accurate representation with historical information, and thus quickly judging whether the liquid level fluctuation is abnormal or not.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S1, the crystallizer liquid level fluctuation data includes offline historical data and online acquired data, and may be applied to offline historical data analysis, and may also be applied to online evaluation of the crystallizer liquid level fluctuation condition, so as to reduce the influence of 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 method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in the step S1, the crystallizer liquid level fluctuation data includes a crystallizer liquid level fluctuation actual value, a crystallizer liquid level fluctuation set value, and the like.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S2, the fast fourier transform is:
wherein x (λ) is a spectral function; x (t) is a crystallizer fluctuation signal; e.g. of the type -iλt Is a Fourier transform kernel function; λ is a frequency variable; t is a time variable.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in the step S3, the technical solution of the present invention can be implemented by using a wavelet entropy analysis method commonly used in the prior art, and the following description is given by taking a wavelet entropy analysis method commonly used in the art as an example, where in the wavelet entropy analysis method, the expression of discrete wavelet transform is:
in the formula, WT x (j, k) is a discrete wavelet transform for the original fluctuating signal x (t); x (t) is a crystallizer fluctuation signal;
is a wavelet basis function; j is the scale; k is time.
Let E 1 ，E 2 ，...，E j For the wavelet spectrum of the signal x (t) on the j scale, E is on the scale domain j A division of the signal energy may be formed; after wavelet decomposition, the sum of wavelet coefficient energies at j scale of signal x (t) is:
in the formula, N is the number of wavelet coefficients under the j scale;
D j (k) is a set of wavelet coefficients at the j-scale.
According to the characteristics of wavelet transformation, E is the power E of each component j And p is j ＝E j E, then ∑ j p j 1, therefore, a wavelet entropy W is defined EE Comprises the following steps:
W EE ＝-∑ j p j log(pj) (4)
the method utilizes the formula (1) to decompose the original fluctuation signal, determines the information such as frequency, amplitude and the like corresponding to the crystallizer liquid level fluctuation, combines the formulas (2) to (4), refines time and scale through wavelet entropy analysis, accurately represents the transformation relation of the frequency and the amplitude in the formula (1), and can quickly judge whether the crystallizer liquid level fluctuation is abnormal or not.
As a preferable scheme of the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in step S3, the history information includes history normal information and history abnormal information.
As a preferable scheme of the method for judging the abnormal fluctuation of the liquid level of the crystallizer, the method comprises the following steps: in the step S4, the process parameters include, but are not limited to, process parameters and equipment parameters, the process parameters include, but are not limited to, casting blank pulling speed, stopper rod position, nozzle nodule size, casting blank bulging parameters, and the like, and the equipment parameters include, but are not limited to, continuous casting machine setting parameters, and the like.
A system for judging the abnormal fluctuation of the liquid level of a crystallizer comprises:
the data processing module is used for analyzing the crystallizer liquid level fluctuation data based on a fast Fourier transform analysis method to obtain information such as frequency, amplitude and the like of the crystallizer liquid level fluctuation;
the precise representation module is used for accurately representing information such as frequency, 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 historical information and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
As a preferable embodiment of the system for judging the abnormal fluctuation of the liquid level of the crystallizer according to the present invention, the system further includes:
and the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy value of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy value of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason causing the abnormal fluctuation of the liquid level of the crystallizer.
According to another aspect of the invention, the invention provides the following technical solutions:
an information data processing terminal for realizing the crystallizer liquid level abnormal fluctuation distinguishing method.
A computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to execute the above-described crystallizer liquid level abnormal fluctuation discrimination method.
The invention may be implemented in whole or in part by software, hardware, firmware or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
Example 1
The embodiment is used for the slab continuous casting production process (the section size of a casting blank is 1500mm multiplied by 220mm), and comprises the following steps:
on the premise of stable casting on site, acquiring crystallizer liquid level fluctuation and related process parameters thereof within a period of time at a certain acquisition frequency;
the method comprises the steps of analyzing liquid level fluctuation data of the crystallizer based on an analysis method combining fast Fourier transform and wavelet entropy, extracting frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods by applying the fast Fourier transform, combining information such as frequency and the like by utilizing the wavelet entropy to make unified representation, and comparing the unified representation with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that accurate judgment is made on the liquid level fluctuation of the crystallizer.
As shown in FIG. 3, the fluctuation frequency mainly exists in the region of 0-1 Hz, the frequency concentration in the region of 0-0.4 Hz, the amplitude of the frequency band is less than 0.2, the amplitude of the region with the frequency of 0.4-0.8 Hz is less than 0.1, the representation is carried out by adopting the wavelet entropy, the wavelet entropy is 0.0136 in the frequency range of 0-0.4 Hz, the wavelet entropy is 0.0061 in the frequency range of 0.4-0.8 Hz, and the wavelet entropy value of the frequency interval is located in the normal fluctuation range of the liquid level.
As shown in FIG. 4, the fluctuation frequency mainly exists in a 0-1 Hz region, the amplitude difference between the frequency of the 0-0.4 Hz region and the frequency of the 0.4-0.8 Hz region is not large, the amplitude of the two frequency regions is less than 0.35, the representation is carried out by adopting wavelet entropy, the wavelet entropy is 0.0971 in the frequency range of 0-0.4 Hz, the wavelet entropy is 0.0963 in the frequency range of 0.4-0.8 Hz, and the wavelet entropy value of the frequency region is located in the liquid level abnormal fluctuation range.
With reference to the process parameters corresponding to the normal and abnormal fluctuation of the crystallizer liquid level in fig. 3 and 4, it can be clearly understood that the reason for the abnormal fluctuation of the crystallizer liquid level in this embodiment is that the position of the stopper rod rises by about 3mm, which indicates that there is a certain degree of nodule in the submerged nozzle, and the change in the position of the stopper rod in the abnormal section is aggravated than the fluctuation in the normal section, and there is a possibility that part of the nodule may drop at the stopper, thereby affecting the fluctuation of the crystallizer liquid level.
Example 2
The embodiment is used for the slab continuous casting production process (the section size of a casting blank is 1500mm multiplied by 220mm), and comprises the following steps:
on the premise of stable casting on site, acquiring crystallizer liquid level fluctuation and related process parameters thereof within a period of time at a certain acquisition frequency;
the method comprises the steps of analyzing liquid level fluctuation data of the crystallizer based on an analysis method combining fast Fourier transform and wavelet entropy, extracting frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods by applying the fast Fourier transform, combining information such as frequency and the like by utilizing the wavelet entropy to make unified representation, and comparing the unified representation with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that accurate judgment is made on the liquid level fluctuation of the crystallizer.
As shown in FIG. 5, the fluctuation frequency mainly exists in the region of 0 to 1Hz, the frequency concentration in the region of 0 to 0.4Hz, the amplitude of the frequency band is less than 0.2, the amplitude of the frequency in the region of 0.4 to 0.8Hz is less than 0.1, the representation is carried out by adopting wavelet entropy, the wavelet entropy is 0.0179 in the frequency range of 0 to 0.4Hz, the wavelet entropy is 0.0071 in the frequency range of 0.4 to 0.8Hz, and the wavelet entropy value of the frequency interval is located in the normal fluctuation range of the liquid level.
As shown in FIG. 6, the fluctuation frequency mainly exists in a 0-1 Hz region, the amplitude difference between the frequency of the 0-0.4 Hz region and the frequency of the 0.4-0.8 Hz region is not large, the amplitude of the two frequency regions is less than 0.4, the representation is carried out by adopting wavelet entropy, the wavelet entropy is 0.1007 in the frequency range of 0-0.4 Hz, the wavelet entropy is 0.1200 in the frequency range of 0.4-0.8 Hz, and the wavelet entropy value of the frequency region is located in the abnormal fluctuation range of the liquid level.
With reference to the process parameters corresponding to the normal and abnormal fluctuation of the liquid level of the crystallizer in fig. 5 and 6, it can be clearly seen that the reason for the abnormal fluctuation of the liquid level of the crystallizer in this embodiment is that the temperature of the tundish drops by about 15 ℃, and at this time, the temperature range of the tundish is at the lower limit of the superheat degree, which may even be lower than the specified superheat degree, and the fluidity of the molten steel is deteriorated, which affects the floating removal of inclusions, accelerates the nodulation rate of the nozzle, and aggravates the change of the position of the stopper rod, thereby generating the abnormal fluctuation of the liquid level of the crystallizer.
Example 3
The embodiment is based on a slab crystallizer (the section size of a casting blank is 1200mm multiplied by 230mm) continuous casting production process with an electromagnetic braking device in a certain factory, and comprises the following steps:
on the premise of stable casting on site, acquiring crystallizer liquid level fluctuation and related process parameters thereof within a period of time at a certain acquisition frequency;
the method comprises the steps of analyzing liquid level fluctuation data of the crystallizer based on an analysis method combining fast Fourier transform and wavelet entropy, extracting frequency intervals and amplitude ranges corresponding to liquid level fluctuation in different time periods by applying the fast Fourier transform, combining information such as frequency and the like by utilizing the wavelet entropy to make unified representation, and comparing the unified representation with wavelet entropy values corresponding to historical normal and abnormal fluctuation, so that accurate judgment is made on the liquid level fluctuation of the crystallizer.
As shown in FIG. 7, the fluctuation frequency mainly exists in the region of 0-1 Hz, the frequency in the region of 0-0.4 Hz is concentrated, the amplitude of the frequency band is less than 0.25, the amplitude of the region with the frequency of 0.4-0.8 Hz is less than 0.15, the wavelet entropy is adopted for representation, the wavelet entropy is 0.0507 in the frequency range of 0-0.4 Hz, the wavelet entropy is 0.0143 in the frequency range of 0.4-0.8 Hz, and the wavelet entropy value of the frequency interval is located in the normal fluctuation range of the liquid level.
As shown in FIG. 8, the fluctuation frequency mainly exists in the region of 0 to 1.5Hz, the frequency is concentrated in the region of 0 to 0.4Hz, the amplitude of the frequency band is less than 1, the amplitude of the frequency in the region of 0.4 to 0.8Hz is less than 0.3, the representation is carried out by adopting wavelet entropy, the wavelet entropy is 0.1912 in the frequency range of 0 to 0.4Hz, the wavelet entropy is 0.0360 in the frequency range of 0.4 to 0.8Hz, and the wavelet entropy value of the frequency interval is located in the liquid level abnormal fluctuation range.
With reference to the process parameters corresponding to the normal and abnormal fluctuations of the liquid level of the crystallizer in fig. 7 and 8, it can be clearly understood that the reason for the abnormal fluctuation of the liquid level of the crystallizer in this embodiment is that the pulling speed is increased by 0.2m/min, and when the pulling speed is increased from 1.4m/min to 1.6m/min, the amplitude of the frequency region of 0 to 0.4Hz and the corresponding wavelet entropy value are increased by a relatively large margin, resulting in the abnormal fluctuation of the crystallizer.
The normal and abnormal fluctuation of the liquid level of the crystallizer can be accurately judged by the analysis method which intuitively embodies the combination of the fast Fourier transform and the wavelet entropy through the 3 embodiments, the feasibility of the judgment method is proved, the casting blank quality in the continuous casting production process can be further judged, the method can be adopted based on different types of crystallizers, relevant process parameters corresponding to the normal and abnormal fluctuation are analyzed and compared according to the judgment result, the reason for generating the abnormal fluctuation is searched, the abnormal fluctuation of the crystallizer can be effectively controlled, and the casting blank quality and the continuous casting production efficiency are improved.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the present specification and directly/indirectly applied to other related technical fields within the spirit of the present invention are included in the scope of the present invention.
Claims (10)
1. A method for judging the abnormal fluctuation of the liquid level of a crystallizer is characterized by comprising the following steps:
s1, analyzing crystallizer liquid level fluctuation data by adopting a fast Fourier transform analysis method to obtain frequency and amplitude information of crystallizer liquid level fluctuation;
s2, accurately representing the frequency and amplitude information of the liquid level fluctuation of the crystallizer by adopting a wavelet entropy analysis method;
and S3, comparing the accurately characterized information with historical information, and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
2. The method for determining the abnormal fluctuation of the liquid level in the crystallizer as set forth in claim 1, further comprising,
s4, comparing the process parameters corresponding to the wavelet entropy of the crystallizer liquid level abnormal fluctuation with the process parameters corresponding to the wavelet entropy of the crystallizer liquid level normal fluctuation, and finding out the reason causing the crystallizer liquid level abnormal fluctuation.
3. The method for determining the abnormal fluctuation of the mold liquid level according to claim 1 or 2, wherein in the step S1, the mold liquid level fluctuation data includes offline historical data and online collected data.
4. The method for determining the abnormal fluctuation of the mold liquid level according to claim 1 or 2, wherein in the step S2, the fast fourier transform is performed by:
wherein x (λ) is a spectral function; x (t) is a crystallizer fluctuation signal; e.g. of the type -iλt Is a Fourier transform kernel function; λ is a frequency variable; t is a time variable.
5. The method for discriminating the abnormal fluctuation of the liquid level in the crystallizer according to claim 1 or 2, wherein in the step S3, in the wavelet entropy analysis method, the expression of the discrete wavelet transform is as follows:
in the formula, WT x (j, k) is a discrete wavelet transform for the original undulation signal x (t); x (t) is a crystallizer fluctuation signal;
is a wavelet basis function; j is the scale; k is time;
let E 1 ，E 2 ，...，E j For the wavelet spectrum of the signal x (t) on the j scale, E is on the scale domain j Can form
A division of the signal energy; after wavelet decomposition, the sum of wavelet coefficient energies at j scale of signal x (t) is:
in the formula, N is the number of wavelet coefficients under the j scale;
D j (k) is a set of wavelet coefficients at the j-scale.
According to the characteristics of wavelet transformation, E is the power E of each component j And p is j ＝E j E, then ∑ j p j 1, thus, a wavelet entropy W is defined EE Comprises the following steps:
W EE ＝-∑ j p j log(p j ) (4)。
6. the method for determining the abnormal fluctuation of the liquid level of the crystallizer according to claim 2, wherein in the step S4, the process parameters comprise a casting blank pulling speed, a stopper position, a nozzle nodule size, a casting blank bulging parameter and a continuous casting machine setting parameter.
7. A system for judging the abnormal fluctuation of the liquid level of a crystallizer, which is used for realizing the method for judging the abnormal fluctuation of the liquid level of the crystallizer according to any one of claims 1 to 6, and comprises the following steps:
the data processing module is used for analyzing the crystallizer liquid level fluctuation data based on a fast Fourier transform analysis method to obtain frequency and amplitude information of the crystallizer liquid level fluctuation;
the precise representation module is used for accurately representing the frequency and amplitude information of the crystallizer liquid level fluctuation based on a wavelet entropy analysis method;
and the abnormal fluctuation judging module is used for comparing the accurately represented information with historical information and judging whether the liquid level fluctuation of the crystallizer is abnormal or not.
8. The system for discriminating the abnormal fluctuation of the liquid level of the crystallizer as claimed in claim 7, further comprising:
and the abnormal fluctuation reason analysis module is used for comparing the process parameters corresponding to the wavelet entropy value of the abnormal fluctuation of the liquid level of the crystallizer with the process parameters corresponding to the wavelet entropy value of the normal fluctuation of the liquid level of the crystallizer, and finding out the reason causing the abnormal fluctuation of the liquid level of the crystallizer.
9. An information data processing terminal for implementing the method for discriminating the abnormal fluctuation of the liquid level of the crystallizer according to any one of claims 1 to 6.
10. A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to execute the crystallizer liquid level abnormal fluctuation discrimination method of any one of claims 1 to 6.
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