Crystallizer liquid level abnormal fluctuation discrimination and reason tracing system, information data processing terminal and computer readable storage medium

Abstract

The invention relates to a crystallizer liquid level abnormal fluctuation judgment and reason tracing system, an information data processing terminal and a computer readable storage medium, and belongs to the technical field of ferrous metallurgy continuous casting. The data processing module is used for calculating the crystallizer liquid level fluctuation index to obtain the maximum value Jmax of the liquid level fluctuation index within the continuous casting billet production time; the analysis module is used for analyzing crystallizer liquid level fluctuation and corresponding process parameters based on a discrete wavelet transform method to obtain frequency information of the crystallizer liquid level fluctuation; the slag entrapment judgment module is used for comparing the crystallizer liquid level fluctuation index with the slag entrapment defect index to judge whether slag entrapment occurs on the crystallizer liquid level or not; the machine clearing guiding module is used for executing the slag entrapment severity degree of the continuous casting blank and the judgment rule of casting blank treatment before rolling, and providing treatment guidance for the casting blank before rolling; and the liquid level abnormity reason tracing module is used for executing the judgment rule of the crystallizer liquid level abnormity fluctuation reason and tracing the inducement of liquid level abnormity.

Description

Technical Field

[0001] This invention relates to the field of continuous casting technology in iron and steel metallurgy, and in particular to a system for identifying and tracing the causes of abnormal fluctuations in the liquid level of a crystallizer, an information data processing terminal, and a computer-readable storage medium. Background Technology

[0002] Automotive steel sheets are representative of high-quality sheet metal products, and their surface quality requirements are quite stringent. Automotive steel sheets are mainly produced through continuous casting, hot rolling, and / or cold rolling processes. During continuous casting, slag entrapment at the surface of the liquid crystallizer can reduce the surface quality of the automotive steel sheets.

[0003] In the continuous casting process, existing detection technologies cannot identify slag entrapment defects on the surface of continuously cast billets. Only after the billets are rolled into plates can surface linear defects caused by slag entrapment on the crystallizer surface be identified using a hot-rolled surface inspection system. Due to the low accuracy of identifying abnormal fluctuations in the crystallizer surface, steel companies machine-clean all continuously cast billets before sending them for rolling to meet customers' "zero tolerance" requirements for defects in steel coils. However, machine cleaning of continuously cast billets reduces metal yield. Therefore, simultaneously achieving the determination and tracing of abnormal fluctuations in the crystallizer surface, predicting slag entrapment defects on the surface of continuously cast billets, and performing pre-rolling treatment on defective billets are of great significance for improving the quality of continuously cast billets.

[0004] Currently, the amplitude of liquid level fluctuations in crystallizers is commonly used to analyze and evaluate the actual situation of liquid level fluctuations. However, its identification accuracy is low, making it difficult to identify the problem accurately. Furthermore, it cannot trace the cause of the fluctuations. Summary of the Invention

[0005] Based on the above analysis, the present invention aims to provide a system, information data processing terminal, and computer-readable storage medium for identifying and tracing abnormal fluctuations in crystallizer liquid level, in order to solve the problems of difficulty in accurately identifying abnormal fluctuations in liquid level and the inability to trace the causes.

[0006] On the one hand, this invention provides a system for identifying and tracing the causes of abnormal fluctuations in the liquid level of a crystallizer.

[0007] The system includes a data processing module, a slag identification module, a machine cleaning guidance module, a liquid level anomaly cause tracing module, and a process parameter adjustment module.

[0008] The data processing module is used to calculate the liquid level fluctuation index in the crystallizer and obtain the maximum value J of the liquid level fluctuation index during the continuous casting billet production time. maxIt is used to analyze the liquid level height and corresponding process parameters of the crystallizer based on the discrete wavelet transform method, and to obtain the frequency information of the liquid surface fluctuation in the crystallizer.

[0009] The slag entrapment discrimination module is used to compare the crystallizer liquid level fluctuation index and the slag entrapment defect index to determine whether slag entrapment has occurred on the crystallizer liquid level.

[0010] The machine cleaning guidance module is used to execute the judgment rules of the severity of slag entrapment in continuous casting billets and the pre-rolling billet treatment, and to provide pre-rolling treatment guidance for billets.

[0011] The liquid level anomaly cause tracing module is used to execute the determination rules for abnormal fluctuations in the liquid level of the crystallizer and trace the cause of the abnormal liquid level.

[0012] The process parameter adjustment module is used to optimize process parameters in real time after tracing the cause of abnormal liquid level in the crystallizer.

[0013] Furthermore, the data processing module collects the liquid level height, obtains the slope and amplitude of the crystallizer liquid level based on the liquid level height, and then calculates the crystallizer liquid level fluctuation index based on the slope and amplitude of the crystallizer liquid level. The crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level. index =K max ×ΔL;

[0014] J index K is the crystallizer liquid level fluctuation index. max ΔL is the maximum value of the liquid level slope within the time period T; ΔL is the maximum value of the crystallizer liquid level amplitude within the time period T.

[0015] Furthermore, the data processing module, taking each continuously cast billet as a unit, extracts the maximum value J of the liquid level fluctuation index during the billet production time based on the calculated crystallizer liquid level fluctuation index. max ;

[0016] J max =max(J1, J2...J n ).

[0017] Furthermore, the data processing module calculates the crystallizer fluctuation height based on the collected crystallizer liquid level height, and then obtains the frequency Rw and amplitude Ra corresponding to the crystallizer liquid level fluctuation using the discrete wavelet transform method. The calculation formula for the discrete wavelet transform analysis method is as follows:

[0018]

[0019] In the formula, W t (a,b) represents the discrete wavelet transform of the liquid level fluctuation in the crystallizer; f(t) represents the liquid level fluctuation data in the crystallizer; ψa,b (t) is a wavelet basis function, a is a scaling factor; b is a translation factor; t is a time node.

[0020] Furthermore, the selected type of the wavelet basis function is the Sym5 wavelet basis function, and the maximum value of the frequency after discrete wavelet transform is 5.0 Hz.

[0021] Furthermore, the slag entrainment discrimination module extracts the number of J where the liquid level fluctuation index of the mold is greater than or equal to the slag entrainment defect index within the production time of one slab. index of them;

[0022]

[0023] In the formula, P is the sampling point corresponding to J index ; P tot is the total number of sampling points; J slag is the slag entrainment defect index, mm 2 / s; J slag ranges from 20 to 40 mm 2 / s.

[0024] Furthermore, the determination rule for the severity of slag entrainment adopted by the machine cleaning guidance module is:

[0025] When J max < J slag , it is determined as a normal slab and no machine cleaning is required;

[0026] When J slag ≤ J max ≤ J slag + 30 mm 2 / s and N ≤ 5, it is determined as mild slag entrainment and no machine cleaning is required;

[0027] When J slag ≤ J max ≤ J slag + 30 mm 2 / s and 5 < N, it is determined as mild slag entrainment and machine cleaning is required once;

[0028] When J slag + 30 mm 2 / s < J max ≤ J slag + 50 mm 2 / s and N ≤ 5, it is determined as moderate slag entrainment and no machine cleaning is required;

[0029] When J slag + 30 mm 2 / s < J max ≤ J slag + 50 mm 2When 5 < N ≤ 15 and the speed is / s, it is determined as moderate slag entrainment, and the machine is cleaned once.

[0030] When J slag +30mm 2 / s < J max ≤ J slag +50mm 2 / s and 15 < N, it is determined as moderate slag entrainment, and the machine is cleaned twice.

[0031] When J slag +50mm 2 / s < J max and N ≤ 5, it is determined as severe slag entrainment, and the machine is not cleaned.

[0032] When J slag +50mm 2 / s < J max and 5 < N ≤ 15, it is determined as severe slag entrainment, and the machine is cleaned once.

[0033] When J slag +50mm 2 / s < J max and 15 < N, it is determined as severe slag entrainment, and the machine is cleaned twice.

[0034] Furthermore, when the peak value of the amplitude Ra in the frequency band is greater than ±3mm, the liquid level fluctuates abnormally. The liquid level abnormal cause tracing module uses the determination rule to trace the cause of the abnormal liquid level fluctuation. The determination rule is:

[0035] When 0 < Rw < 0.1Hz, the reason for the abnormal liquid level fluctuation is that the casting speed, the width of the continuous casting billet, the ladle tonnage or the immersion depth of the nozzle changes;

[0036] When 0 < Rw < 0.1Hz, if the casting speed, the width of the continuous casting billet and the ladle tonnage do not change, the reason for the abnormal liquid level fluctuation is determined to be the shedding of the nodule on the tip or the body of the stopper rod, the inner wall of the upper nozzle or the immersion nozzle;

[0037] When 0.1Hz ≤ Rw ≤ 0.4Hz, the reason for the abnormal liquid level fluctuation is the unstable bulging between the rolls;

[0038] When 0.4Hz < Rw ≤ 1.0Hz, the reason for the abnormal liquid level fluctuation is that the stopper rod, the upper nozzle of the ladle or the immersion nozzle is severely nodular;

[0039] When 1.0Hz < Rw ≤ 5.0Hz, the reason for the abnormal liquid level fluctuation is the frequency, which is the natural frequency of the mold vibration.

[0040] The present invention provides an information data processing terminal for realizing the discrimination of abnormal liquid level fluctuation in the mold and the tracing of the cause.

[0041] The present invention also provides a computer-readable storage medium including computer instructions, which, when executed on a computer, cause the computer to execute a system for identifying and tracing abnormal fluctuations in the liquid level of a crystallizer.

[0042] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0043] 1. This invention uses the discrete wavelet transform method to analyze the time-frequency characteristics of the crystallizer liquid level height, enabling the tracing of the causes of abnormal liquid level fluctuations and the optimization of process parameters; thus guiding production. This method comprehensively and multidimensionally solves the problems of abnormal liquid level fluctuations and slag entrapment in the crystallizer, achieving stable control of crystallizer liquid level fluctuations and improving the quality of continuously cast billets, thereby reducing quality complaints and objections from users.

[0044] 2. The system provided by this invention can accurately identify slag entanglement defects by collecting continuous casting production data, calculating the liquid level fluctuation index of the crystallizer, extracting the maximum value of the liquid level fluctuation index during the billet production time, and determining the severity of slag entanglement in the continuous casting billet, thereby providing guidance for the pre-rolling treatment of the continuous casting billet.

[0045] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0046] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0047] Figure 1 This is a flowchart of the method for determining the degree of slag entrapment on the liquid surface of the crystallizer and the pre-rolling treatment of the continuously cast billet according to the present invention.

[0048] Figure 2 This is a flowchart of the method for tracing the causes of abnormal fluctuations in the liquid level of the crystallizer according to the present invention;

[0049] Figure 3 The figure shows the comparative analysis results of the crystallizer liquid level fluctuation index and the slag curling defect on the hot-rolled plate in Example 1.

[0050] Figure 4 This is a block diagram of the system structure of the present invention. Detailed Implementation

[0051] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0052] In the continuous casting process, existing detection technologies cannot identify slag entrapment defects on the surface of continuously cast billets. Only after the billets are rolled into plates can surface linear defects caused by slag entrapment on the crystallizer surface be identified using a hot-rolled surface inspection system. Due to the low accuracy of identifying abnormal fluctuations in the crystallizer surface, steel companies machine-clean all continuously cast billets before sending them for rolling to meet customers' "zero tolerance" requirements for defects in steel coils. However, machine cleaning of continuously cast billets reduces metal yield. Therefore, achieving the ability to determine and trace the causes of abnormal fluctuations in the crystallizer surface, as well as predicting slag entrapment defects on the surface of continuously cast billets and performing pre-rolling treatment on defective billets, is of great significance for improving the quality of continuously cast billets.

[0053] Currently, the amplitude of liquid level fluctuations in crystallizers is commonly used to analyze and evaluate the actual situation of liquid level fluctuations. However, its identification accuracy is low, making it difficult to identify the problem accurately. Furthermore, it cannot trace the cause of the fluctuations.

[0054] Therefore, the present invention provides a system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level. The system includes a data processing module, a slag entrapment identification module, a machine cleaning guidance module, a liquid level abnormality cause tracing module, and a process parameter adjustment module.

[0055] The data processing module is used to calculate the liquid level fluctuation index in the crystallizer and obtain the maximum value J of the liquid level fluctuation index during the continuous casting billet production time. max It is used to analyze the liquid level height and corresponding process parameters of the crystallizer based on the discrete wavelet transform method, and to obtain the frequency information of the liquid surface fluctuation in the crystallizer.

[0056] The slag entrapment discrimination module is used to compare the crystallizer liquid level fluctuation index and the slag entrapment defect index to determine whether slag entrapment has occurred on the crystallizer liquid level.

[0057] The machine cleaning guidance module is used to execute the judgment rules of the severity of slag entrapment in continuous casting billets and the pre-rolling billet treatment, and to provide pre-rolling treatment guidance for billets.

[0058] The liquid level anomaly cause tracing module is used to execute the determination rules for abnormal fluctuations in the liquid level of the crystallizer and trace the cause of the abnormal liquid level.

[0059] The process parameter adjustment module is used to optimize process parameters in real time after tracing the cause of abnormal liquid level in the crystallizer.

[0060] It should be noted that this invention uses the discrete wavelet transform method to analyze the time-frequency characteristics of crystallizer liquid level fluctuations, enabling the tracing of the causes of abnormal liquid level fluctuations and the optimization of process parameters; thus guiding production. This method comprehensively and multidimensionally solves the problems of abnormal liquid level fluctuations and slag entrapment in crystallizers, achieving stable control of crystallizer liquid level fluctuations and improving the quality of continuously cast billets, thereby reducing quality complaints and objections from users.

[0061] This invention provides a method for accurately identifying slag entanglement defects and providing pre-rolling treatment guidance for continuous casting billets by collecting continuous casting production data, calculating the liquid level fluctuation index in the crystallizer, extracting the maximum value of the liquid level fluctuation index during the billet production time, and determining the severity of slag entanglement in continuous casting billets.

[0062] Specifically, the data processing module collects the liquid level height, obtains the slope and amplitude of the crystallizer liquid level based on the liquid level height, and calculates the crystallizer liquid level fluctuation index based on the slope and amplitude of the crystallizer liquid level. The crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level. index =K max ×ΔL;

[0063] J index K is the crystallizer liquid level fluctuation index. max ΔL is the maximum value of the liquid level slope within the time period T; ΔL is the maximum value of the crystallizer liquid level amplitude within the time period T.

[0064] Specifically, the formula for calculating the slope of the crystallizer liquid level is as follows:

[0065] In the formula, K is the slope of the liquid level in the crystallizer, mm / s; L n+1 The value of the crystallizer liquid level at the previous time, in mm; L n ΔT represents the actual liquid level in the crystallizer at the later time, in mm; ΔT is the casting time interval, in s, ΔT = 0.01~0.1s.

[0066] Specifically, in step S1, the liquid level difference is grouped using a time sliding window, and the maximum value K of the liquid level slope within the time interval T is extracted, with ΔT as the sliding time step. max =max(K1, K2...K) n ).

[0067] It should be noted that ΔT is the casting time interval, which is also the slip time step. In this invention, ΔT is controlled to be between 0.01 and 0.1 s. If ΔT is less than 0.01 s, the amount of data calculation becomes too large, affecting the calculation efficiency. If ΔT is greater than 0.1 s, data is easily missed, resulting in inaccurate calculation results.

[0068] Specifically, in step S1, the maximum amplitude of the crystallizer liquid level is calculated by using T as the time sliding window and ΔT as the sliding time step, to find the maximum value L of the liquid level within the time period T. max =max(L1, L2…L) n The minimum value of the liquid level L min =min(L1, L2…L) n The minimum liquid level is calculated by subtracting the maximum liquid level from the minimum liquid level within the group, i.e., ΔL = L. max -L min ;

[0069] In the formula, L max The maximum liquid level within time interval T, in mm; L min The minimum liquid level within time interval T, in mm.

[0070] It should be noted that in order to obtain a continuous and complete crystallizer level waveform, that is, the waveform change from trough to peak or from peak to trough, the time sliding window (T) should satisfy 3s≤T≤5s.

[0071] Specifically, the data processing module takes each continuously cast billet as a unit and extracts the maximum value J of the liquid level fluctuation index during the billet production time based on the calculated crystallizer liquid level fluctuation index. max ;

[0072] J max =max(J1, J2...J n ).

[0073] Specifically, the slag entrapment discrimination module extracts J values ​​where the crystallizer liquid level fluctuation index is greater than or equal to the slag entrapment defect index during the production time of a slab, based on the crystallizer liquid level fluctuation index and the slag entrapment defect index. index The number of;

[0074]

[0075] In the formula, P is related to J index Corresponding sampling point; P tot J represents the total number of sampling points; slag The defect index for slag contamination is expressed in mm. 2 / s;J slag The value range is 20–40 mm. 2 / s.

[0076] Preferably, the types of slag entrainment defects on the hot-rolled sheet include edge slag entrainment, middle slag entrainment, small slag entrainment distributed on the upper and lower surfaces of the hot-rolled sheet, as well as edge peeling and head peeling caused by steelmaking reasons.

[0077] It should be noted that different steel grades have different names for the linear slag entrainment defects and peeling defects on the hot-rolled sheet. Here, it only refers to the defects caused by mold powder slag entrainment.

[0078] Specifically, the value of the slag entrainment defect index of the hot-rolled sheet corresponding to determining whether the continuous casting billet has slag entrainment defects is J slag , J slag The value range is 20 - 40 mm 2 / s.

[0079] It should be noted that by comparing and analyzing the maximum value of the mold liquid level fluctuation index calculated for each continuous casting billet and the surface inspection situation of the slag entrainment defects on the hot-rolled sheet, it can be given within a range according to the probability of slag entrainment occurrence. For example, 20 mm 2 / s ≤ J slag < 40 mm 2 / s. The smaller the J slag value, the higher the accuracy rate, but the false alarm rate is large; the larger the J slag value, the lower the accuracy rate, but the missed alarm rate is large.

[0080] Specifically, the determination rule for the severity of slag entrainment adopted by the machine cleaning guidance module is:

[0081] When J max < J slag , it is determined as a normal casting billet and no machine cleaning is required;

[0082] When J slag ≤ J max ≤ J slag + 30 mm 2 / s, and N ≤ 5, it is determined as mild slag entrainment and no machine cleaning is required;

[0083] When J slag ≤ J max ≤ J slag + 30 mm 2 / s, and 5 < N, it is determined as mild slag entrainment and machine cleaning is required once;

[0084] When J slag + 30 mm 2 / s < J max ≤ J slag + 50 mm 2 / s, and N ≤ 5, it is determined as moderate slag entrainment and no machine cleaning is required;

[0085] When J slag + 30 mm2 / s < J max ≤ J slag +50 mm 2 / s, when 5 < N ≤ 15, it is determined as moderate slag entrainment, and the machine cleaning is carried out once;

[0086] When J slag +30 mm 2 / s < J max ≤ J slag +50 mm 2 / s, when 15 < N, it is determined as moderate slag entrainment, and the machine cleaning is carried out twice;

[0087] When J slag +50 mm 2 / s < J max , when N ≤ 5, it is determined as severe slag entrainment, and no machine cleaning is carried out;

[0088] When J slag +50 mm 2 / s < J max , when 5 < N ≤ 15, it is determined as severe slag entrainment, and the machine cleaning is carried out once;

[0089] When J slag +50 mm 2 / s < J max , when 15 < N, it is determined as severe slag entrainment, and the machine cleaning is carried out twice.

[0090] It should be noted that the determination rules for the severity of the slag entrainment defect of the continuous casting billet and the treatment of the casting billet before rolling are as follows: for each continuous casting billet, combined with the size of J max during the production time of the whole continuous casting billet and the number N of J index ≥ J slag counted for the length of each continuous casting billet, comprehensively determine whether the current continuous casting billet needs to be subjected to machine cleaning operation.

[0091] In the present invention, when judging the severity of the slag entrainment of the continuous casting billet, it is necessary to rely on the maximum value J max of the liquid level fluctuation index during the casting billet production time; and the number of J index of the liquid level fluctuation index that is greater than or equal to the slag entrainment defect index during the production time. index

[0092] During the continuous casting process, due to various reasons such as the entrainment of the protective slag, defects such as cracks, scabs, slag inclusions, and bubbles will occur on the surface of the slab. If these defects are not treated, they will be magnified and extended in the subsequent rolling process, resulting in the final products (such as steel plates and strip steels) becoming waste products or defective products. The purpose of "machine cleaning" is to remove these defective surface layers before entering the heating furnace and the rolling mill to ensure the surface quality of the slab. However, if a large amount of machine cleaning operations are carried out on the casting billet, it will lead to a low metal yield and an increase in production costs.​

[0093] Specifically, the data processing module calculates the fluctuation height of the mold based on the collected height of the mold liquid surface, and then obtains the corresponding frequency Rw and amplitude Ra of the mold liquid surface fluctuation according to the discrete wavelet transform method. The calculation formula of the discrete wavelet transform analysis method is as follows:

[0094]

[0095] In the formula, W t (a, b) is the discrete wavelet transform of the mold liquid surface fluctuation; f(t) is the mold liquid surface fluctuation data; ψ a,b (t) is the wavelet basis function, a is the scale factor; b is the translation factor; t is the time node.

[0096] Specifically, the selected type of wavelet basis function is the Sym5 wavelet basis function, and the maximum value of the frequency after discrete wavelet transform is 5.0Hz.

[0097] The process parameters during mold liquid surface slag entrainment and normal casting include continuous casting billet production time, continuous casting billet width, mold liquid level height, stopper rod position, casting speed, submerged entry nozzle immersion depth, stopper rod argon flow rate, stopper rod argon back pressure, tundish upper nozzle argon flow rate, tundish upper nozzle argon back pressure, inter-slab argon flow rate, inter-slab argon back pressure, tundish tonnage, torque of the driving rolls on the inner arc side of different segment sectors, and continuous casting billet reduction amount.

[0098] When the amplitude Ra in the frequency band is greater than the peak value of ±3mm, the liquid level fluctuates abnormally. The liquid level abnormal cause tracing module uses the judgment rule to trace the cause of the abnormal liquid level fluctuation. The judgment rule is as follows:

[0099] When 0 < Rw < 0.1Hz, the reason for the abnormal liquid level fluctuation is that the casting speed, continuous casting billet width, tundish tonnage or submerged entry nozzle immersion depth changes;

[0100] When 0 < Rw < 0.1Hz, if the casting speed, continuous casting billet width, and tundish tonnage do not change, the reason for the abnormal liquid level fluctuation is determined to be the shedding of nodules on the tip or body of the stopper rod, the inner wall of the upper nozzle or the submerged entry nozzle;

[0101] When 0.1Hz ≤ Rw ≤ 0.4Hz, the reason for the abnormal liquid level fluctuation is the unstable bulging between the rolls;

[0102] When 0.4Hz < Rw ≤ 1.0Hz, the reason for the abnormal liquid level fluctuation is that the stopper rod, tundish upper nozzle or submerged entry nozzle is severely coked;

[0103] When 1.0Hz < Rw ≤ 5.0Hz, the reason for the abnormal liquid level fluctuation is the frequency, which is the natural frequency of the mold vibration.

[0104] It should be noted that when 0 < Rw < 0.1 Hz, there are mainly two reasons for the abnormal liquid level fluctuation. On the first hand, first check whether it is due to changes in casting speed, continuous casting slab width, tundish tonnage or submerged nozzle immersion depth. On the second hand, if the liquid level fluctuation is not caused by the above reasons, then it is the fluctuation caused by the shedding of the nodular matter, which can be identified according to whether there is a drastic change (jump) in the stopper rod position curve; and then adjust, change or clean the nodular matter on the head or body of the stopper rod, the inner wall of the upper nozzle or the submerged nozzle.

[0105] When 0.1 Hz ≤ Rw ≤ 0.4 Hz, the reason for the abnormal liquid level fluctuation is the unstable bulging between the rolls. The occurrence of the bulging phenomenon can be identified according to the abnormal torque of the driving rolls on the inner arc side of different segment sectors and the abnormal reduction of the continuous casting slab, and then corresponding adjustments can be made.

[0106] When 0.4 Hz < Rw ≤ 1.0 Hz, the reason for the abnormal liquid level fluctuation is serious nodulation at the stopper rod, the upper tundish nozzle or the submerged nozzle. Whether the stopper rod is nodulated can be identified according to the abnormality of the stopper rod argon flow rate and the stopper rod argon back pressure. Whether the upper tundish nozzle is nodulated can be identified according to the abnormality of the upper nozzle argon flow rate and the upper nozzle argon back pressure. Whether the submerged nozzle is nodulated can be identified according to the abnormality of the inter-plate argon flow rate and the inter-plate argon back pressure. Adjust or control the above parameters to reduce the coefficient of nodulation.

[0107] When 1.0 Hz < Rw ≤ 5.0 Hz, this frequency is the natural characteristic frequency of the mold self-vibration, which belongs to the natural fluctuation signal during the normal operation of the equipment, and is not the abnormal fluctuation of the mold liquid level caused by external factors such as process parameter deviation and equipment failure. Therefore, the fluctuations corresponding to this frequency range can be excluded in the traceability of the abnormal liquid level cause and process regulation, and no special treatment measures need to be taken for the frequencies in this interval.

[0108] The present invention provides an information data processing terminal for realizing the discrimination of abnormal liquid level fluctuation of the mold and the cause traceability system.

[0109] The present invention also provides a computer-readable storage medium, including computer instructions, which when running on a computer, cause the computer to execute the discrimination of abnormal liquid level fluctuation of the mold and the cause traceability system.

[0110] As mentioned above, only the preferred specific embodiments of the present invention are described, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the technical field of the present invention within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A system for discriminating abnormal fluctuations in the mold liquid level and tracing the causes, characterized in that: The system includes a data processing module, a slag entrainment discrimination module, a machine cleaning guidance module, a module for tracing the causes of abnormal liquid level, and a process parameter adjustment module; The data processing module is used to calculate the liquid level fluctuation index in the crystallizer and obtain the maximum value J of the liquid level fluctuation index during the continuous casting billet production time. max It is used to analyze the liquid level height and corresponding process parameters of the crystallizer based on the discrete wavelet transform method, and to obtain the frequency information of the liquid surface fluctuation in the crystallizer. The slag entrainment discrimination module is used to compare the mold liquid level fluctuation index and the slag entrainment defect index to determine whether slag entrainment occurs on the mold liquid level; The machine cleaning guidance module is used to execute the determination rules for the severity of slag entrainment in the continuous casting billet and the treatment of the billet before rolling, and give guidance on the treatment of the billet before rolling; The module for tracing the causes of abnormal liquid level is used to execute the determination rules for the causes of abnormal fluctuations in the mold liquid level and trace the inducements for the abnormal liquid level; The process parameter adjustment module is used to optimize the process parameters in real time after tracing the inducements for the abnormal mold liquid level.

2. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The data processing module collects the liquid level height, obtains the slope and amplitude of the crystallizer liquid level based on the liquid level height, and then calculates the crystallizer liquid level fluctuation index based on the slope and amplitude of the crystallizer liquid level. The crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level. index =K max ×ΔL; J index K is the crystallizer liquid level fluctuation index. max ΔL is the maximum value of the liquid level slope within the time period T; ΔL is the maximum value of the crystallizer liquid level amplitude within the time period T.

3. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The data processing module, taking each continuously cast billet as a unit, extracts the maximum value J of the liquid level fluctuation index during the billet production time based on the calculated crystallizer liquid level fluctuation index. max ; J max =max(J1,J2...J n )。 4. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The data processing module calculates the mold fluctuation height based on the collected mold liquid level height, and then obtains the frequency Rw and amplitude Ra corresponding to the mold liquid level fluctuation according to the discrete wavelet transform method. The calculation formula of the discrete wavelet transform analysis method is: In the formula, W t (a,b) represents the discrete wavelet transform of the liquid level fluctuation in the crystallizer; f(t) represents the liquid level fluctuation data in the crystallizer; ψ a,b (t) represents the wavelet basis function, a is the size factor, b is the translation factor, and t is the time node.

5. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 4, characterized in that, The selected type of wavelet basis function is the Sym5 wavelet basis function, and the maximum value of the frequency after discrete wavelet transform is 5.0Hz.

6. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The slag entrapment discrimination module extracts J values ​​where the crystallizer liquid level fluctuation index is greater than or equal to the slag entrapment defect index during the production time of a slab, based on the crystallizer liquid level fluctuation index and the slag entrapment defect index. index The number of; In the formula, P is related to J index The corresponding sampling point; P tot J represents the total number of sampling points; slag The defect index for slag contamination is expressed in mm. 2 / s;J slag The value range is 20–40 mm. 2 / s.

7. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The determination rules for the severity of slag entrainment adopted by the machine cleaning guidance module are: When J max <J slag At that time, it was determined to be a normal casting billet and was not machine cleaned; When J slag ≤J max ≤J slag +30mm 2 When the density is / s and N≤5, it is judged as slight slag entrainment and should not be machine cleaned; When J slag ≤ J max ≤ J slag + 30 mm 2 / s, when N < 5, it is judged as mild slag entrainment and cleaned by machine once; When J slag +30mm 2 / s <J max ≤J slag +50mm 2 When the density is / s and N≤5, it is judged as moderate slag entrainment and does not require machine cleaning; When J slag +30 mm 2 / s < J max ≤ J slag +50 mm 2 / s, when 5 < N ≤ 15, it is determined as moderate slag entrainment and is cleaned by the machine once; When J slag +30 mm 2 / s < J max ≤ J slag +50 mm 2 / s, when 15 < N, it is judged as moderate slag entrainment, and the machine is cleaned twice; When J slag +50mm 2 / s <J max When N≤5, it is judged as heavy slag entrainment and not machine cleaning is required; When J slag +50 mm 2 / s < J max , when 5 < N ≤ 15, it is judged as severe slag entrainment and the machine is cleaned once; When J slag +50 mm 2 / s < J max , and when N < 15, it is determined as severe slag entrainment, and the machine is cleaned twice.

8. The system for identifying and tracing the causes of abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, When the peak value of the amplitude Ra in the frequency band is greater than ±3mm, the liquid level fluctuates abnormally. The module for tracing the causes of abnormal liquid level uses the determination rules to trace the causes of the abnormal liquid level fluctuation. The determination rules are: [[ID= ​ ​ ​ ​ ​ ​

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