Method for judging abnormal fluctuation of liquid level of crystallizer and application

Abstract

The invention relates to a crystallizer liquid level abnormal fluctuation judgment method and application, and belongs to the technical field of ferrous metallurgy continuous casting. The crystallizer liquid level abnormal fluctuation judgment method comprises the steps that continuous casting production data are collected, and a crystallizer liquid level fluctuation index is calculated; comparing and analyzing the maximum value of the crystallizer liquid level fluctuation index calculated by each continuous casting billet and the judgment result of the slag entrapment defect on the corresponding hot-rolled plate so as to determine the critical threshold value of the corresponding liquid level fluctuation index when the slag entrapment defect of the continuous casting billet occurs, namely the slag entrapment defect index; and counting the number of crystallizer liquid level fluctuation indexes greater than or equal to the slag entrapment defect index on each continuous casting billet, comparing and analyzing the number of the slag entrapment defects on the corresponding hot-rolled plate, and establishing a judgment rule of the slag entrapment severity of the continuous casting billet.

Description

Technical Field

[0001] This invention relates to the field of continuous casting technology in iron and steel metallurgy, and in particular to a method and application for identifying abnormal fluctuations in the liquid level of a crystallizer. 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] During the continuous casting production process, existing detection technologies cannot identify slag entrapment defects on the surface of the continuous casting billet. Only after the continuous casting billet is rolled into a plate can the surface linear defects caused by slag entrapment on the liquid surface of the crystallizer be identified by the hot rolling surface detection system.

[0004] Currently, the amplitude of liquid level fluctuations in crystallizers is commonly used to analyze and evaluate the actual situation of liquid surface fluctuations. However, its recognition accuracy is low, and it cannot be recognized accurately, resulting in a low accuracy rate. Summary of the Invention

[0005] Based on the above analysis, the present invention aims to provide a method and application for identifying abnormal fluctuations in the liquid level of a crystallizer, in order to solve the problem of difficulty in accurately identifying abnormal fluctuations in the liquid level.

[0006] On the one hand, the present invention provides a method for identifying abnormal fluctuations in the liquid level of a crystallizer, comprising the following steps:

[0007] S1: Collect continuous casting production data and calculate the crystallizer liquid level fluctuation index;

[0008] S2: Compare and analyze the maximum value of the crystallizer liquid level fluctuation index calculated for each continuous casting billet, and the judgment result of the corresponding slag entrapment defect on the hot-rolled plate, so as to determine the critical threshold of the liquid level fluctuation index corresponding to the occurrence of slag entrapment defect in the continuous casting billet, i.e., the slag entrapment defect index.

[0009] S3: Count the number of crystallizer liquid level fluctuation indices that are greater than or equal to the slag entrapment defect index on each continuous casting billet, and compare and analyze the number of slag entrapment defects on the corresponding hot-rolled plate to establish a judgment rule for the severity of slag entrapment on the continuous casting billet.

[0010] Furthermore, in step S1, the continuous casting production data includes the continuous casting billet production time, continuous casting billet width, crystallizer liquid level height, stopper rod position, casting speed, tundish tonnage, torque of the inner arc side drive rollers of different sector segments, and continuous casting billet reduction. Taking the continuous casting billet as the unit, the above process parameters are matched with the billet number, casting machine flow number, furnace number, and steel grade according to the billet production time.

[0011] Further, in step S1, the crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level, J index =K max ×ΔL;

[0012] 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.

[0013] Furthermore, the formula for calculating the slope of the crystallizer liquid level is as follows:

[0014] In the formula, K is the slope of the liquid level in the crystallizer, mm / s; L n+1 The value of the liquid level in the crystallizer 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.

[0015] Furthermore, 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 ).

[0016] Furthermore, in step S1, the maximum amplitude of the crystallizer liquid level is calculated as follows: using T as the time sliding window and ΔT as the sliding time step, the maximum value L of the liquid level within the time interval T is found. max =max(L1, L2…L) n The minimum 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 ;

[0017] In the formula, L max L represents the maximum liquid level within time interval T, in mm. min The minimum liquid level within time interval T, in mm.

[0018] Furthermore, taking each continuously cast billet as a unit, the maximum value J of the liquid level fluctuation index during the billet production time was extracted. max ;

[0019] J max =max(J1, J2...J n )

[0020] Extract the number of times when the liquid level fluctuation index is greater than or equal to the slag entrainment defect index during the production time of a slab.

[0021]

[0022] 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, in mm 2 / s.

[0023] Furthermore, the value of the slag entrainment defect index of the corresponding hot-rolled plate for determining whether the continuous casting billet has a slag entrainment defect is J slag = 20 - 40 mm 2 / s.

[0024] Furthermore, the determination rule for the severity of slag entrainment in the continuous casting billet:

[0025] When J max < J slag , it is determined as a normal casting billet and not machined cleaned;

[0026] When J slag ≤ J max ≤ J slag + 30 mm 2 / s, and N ≤ 5, it is determined as mild slag entrainment and not machined cleaned;

[0027] When J slag ≤ J max ≤ J slag + 30 mm 2 / s, and 5 < N, it is determined as mild slag entrainment and machined cleaned 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 not machined cleaned;

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

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

[0031] When J slag +50mm 2 / s < J max and N ≤ 5, it is determined as severe slag entrainment, and no machine cleaning is carried out.

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

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

[0034] On the other hand, the present invention provides a method for tracing the cause of abnormal liquid level fluctuations, including the method for discriminating abnormal liquid level fluctuations in the mold described in the present invention, and combining the method for discriminating abnormal liquid level fluctuations in the mold and the determination rules for the cause of abnormal liquid level fluctuations in the mold to trace the cause of abnormal liquid level fluctuations.

[0035] Compared with the prior art, the present invention can at least achieve one of the following beneficial effects:

[0036] 1. The present invention provides a method for discriminating abnormal liquid level fluctuations in the mold, collecting continuous casting production data, calculating the liquid level fluctuation index of the mold, extracting the maximum value of the liquid level fluctuation index during the casting production time, and the determination rules for the severity of slag entrainment in continuous casting billets, which can accurately identify slag entrainment defects and realize the processing guidance before rolling of continuous casting billets.

[0037] 2. Based on the method for discriminating abnormal liquid level fluctuations in the mold provided by the present invention, combined with the determination rules for the cause of abnormal liquid level fluctuations in the mold, the time-frequency characteristics of the liquid level height in the mold are analyzed based on the discrete wavelet transform method, realizing the tracing of the cause of abnormal liquid level fluctuations and the optimization of process parameters, and guiding production. This method comprehensively and multi-dimensionally solves the problems of abnormal liquid level fluctuations and liquid level slag entrainment in the mold, realizes stable control of the liquid level fluctuations in the mold and improves the quality of continuous casting billets, reducing quality complaints and quality objections at the user end.

[0038] In the present invention, the above technical solutions can also be combined with each other to achieve more preferred combination schemes. Other features and advantages of the present invention will be described in the subsequent specification, and some advantages can be made obvious from the specification or understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the content specifically pointed out in the specification and the drawings. Brief Description of the Drawings

[0039] 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.

[0040] 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 method for continuously cast billets according to the present invention.

[0041] 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;

[0042] 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. Detailed Implementation

[0043] 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.

[0044] 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.

[0045] During the continuous casting production process, existing detection technologies cannot identify slag entrapment defects on the surface of the continuous casting billet. Only after the continuous casting billet is rolled into a plate can the surface linear defects caused by slag entrapment on the liquid surface of the crystallizer be identified by the hot rolling surface detection system.

[0046] Currently, the amplitude of liquid level fluctuations in crystallizers is commonly used to analyze and evaluate the actual situation of liquid surface fluctuations. However, its recognition accuracy is low, and it cannot be recognized accurately, resulting in a low accuracy rate.

[0047] Therefore, the present invention provides a method for identifying abnormal fluctuations in the liquid level of a crystallizer, comprising the following steps:

[0048] S1: Collect continuous casting production data and calculate the crystallizer liquid level fluctuation index;

[0049] S2: Compare and analyze the maximum value of the liquid level fluctuation index of the crystallizer calculated for each continuous casting billet and the judgment result of the slag entrapment defect on the corresponding hot-rolled plate to determine the critical threshold of the liquid level fluctuation index when the continuous casting billet has a slag entrapment defect, i.e., the slag entrapment defect index.

[0050] S3: Count the number of crystallizer liquid level fluctuation indices that are greater than or equal to the slag entrapment defect index on each continuous casting billet, and compare and analyze them with the number of slag entrapment defects on the corresponding hot-rolled plate to establish a judgment rule for the severity of slag entrapment on the continuous casting billet.

[0051] Compared with the prior art, the present invention provides a method for identifying abnormal fluctuations in the liquid level of a crystallizer. It collects continuous casting production data, calculates the liquid level fluctuation index of the crystallizer, extracts the maximum value of the liquid level fluctuation index during the billet production time, and establishes a rule for judging the severity of slag entrapment in the continuous casting billet. This method can accurately identify slag entrapment defects and provide guidance for the pre-rolling treatment of the continuous casting billet.

[0052] Specifically, in step S1, the continuous casting production data includes the continuous casting billet production time, continuous casting billet width, crystallizer liquid level height, stopper rod position, casting speed, tundish tonnage, torque of the inner arc side drive rollers of different sector segments, and continuous casting billet reduction. Taking the continuous casting billet as the unit, the above process parameters are matched with the billet number, casting machine flow number, furnace number, and steel grade according to the billet production time.

[0053] It should be noted that in this invention, the width of the continuously cast billet is equal to the width of the crystallizer; the stopper rod position refers to the change in the position of the stopper rod during the casting process. When nodules fall off, the stopper rod position curve will change abruptly. The torque of the drive roller on the inner arc side of different sector segments and the reduction of the continuously cast billet are used to evaluate whether the billet bulges.

[0054] Specifically, in step S1, the crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level, J index =K max ×ΔL

[0055] 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.

[0056] Specifically, the formula for calculating the slope of the crystallizer liquid level is as follows:

[0057] In the formula, K is the slope of the liquid level in the crystallizer, mm / s; L n+1 The value of the liquid level in the crystallizer 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.

[0058] 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).

[0059] 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.

[0060] 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 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 ;

[0061] In the formula, L max L represents the maximum liquid level within time interval T, in mm. min The minimum liquid level within time interval T, in mm.

[0062] 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.

[0063] Specifically, taking each continuously cast billet as a unit, the maximum value J of the liquid level fluctuation index during the billet production time is extracted. max ;

[0064] J max =max(J1, J2...J n )

[0065] Extract the J values ​​that are greater than or equal to the slag contamination defect index during the production time of a slab. index The number of;

[0066]

[0067] 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.

[0068] Preferably, in step S2, the types of slag defects on the hot-rolled plate include edge slag, middle slag, small slag distributed on the upper and lower surfaces of the hot-rolled plate, as well as edge peeling and head peeling caused by steelmaking.

[0069] It should be noted that different steel grades have different names for the linear slag inclusion defects and peeling defects on the hot-rolled sheet. Here, it only refers to the defects caused by the entrapment of mold powder.

[0070] Specifically, the value of the slag inclusion defect index of the corresponding hot-rolled sheet for determining whether the continuous casting billet has slag inclusion defects is J slag , J slag The value range is 20 - 40 mm 2 / s.

[0071] 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 inclusion defects on the hot-rolled sheet, it can be given in a range according to the probability of slag inclusion occurrence. For example, 20 mm 2 / s ≤ J slag < 40 mm 2 / s. The smaller the value of J slag , the higher the accuracy rate, but the false alarm rate is large; the larger the value of J slag , the lower the accuracy rate, but the missed alarm rate is large.

[0072] The determination rule for the severity of the slag inclusion defect of the continuous casting billet and the treatment of the billet before rolling is: for each continuous casting billet, combined with the size of J max during the production time of the whole continuous casting billet and the quantity 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.

[0073] Specifically, the determination rule for the severity of the slag inclusion of the continuous casting billet:

[0074] When J max < J slag , it is determined as a normal casting billet and not subjected to machine cleaning;

[0075] When J slag ≤ J max ≤ J slag + 30 mm 2 / s and N ≤ 5, it is determined as mild slag inclusion and not subjected to machine cleaning;

[0076] When J slag ≤ J max ≤ J slag + 30 mm 2 / s and 5 < N, it is determined as mild slag inclusion and subjected to one-time machine cleaning;

[0077] When J slag + 30 mm 2 / s < J max ≤ J slag + 50 mm 2When N ≤ 5 and J ≤ J + 30mm / s, it is determined as moderate slag entrainment and not machine-cleaned;

[0078] When J slag +30mm 2 / s < J max ≤ J slag +50mm 2 / s and 5 < N ≤ 15, it is determined as moderate slag entrainment and machine-cleaned once;

[0079] When J slag +30mm 2 / s < J max ≤ J slag +50mm 2 / s and 15 < N, it is determined as moderate slag entrainment and machine-cleaned twice;

[0080] When J slag +50mm 2 / s < J max and N ≤ 5, it is determined as severe slag entrainment and not machine-cleaned;

[0081] When J slag +50mm 2 / s < J max and 5 < N ≤ 15, it is determined as severe slag entrainment and machine-cleaned once;

[0082] When J slag +50mm 2 / s < J max and 15 < N, it is determined as severe slag entrainment and machine-cleaned twice.

[0083] It should be noted that in this invention, when judging the severity of slag entrainment in continuous casting billets, it is necessary to rely on the maximum value J max of the liquid level fluctuation index during the production time of the billet; 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

[0084] During continuous casting, due to various reasons such as slag entrainment, 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 amplified and extended in subsequent rolling processes, resulting in the final products (such as steel plates and strip steel) becoming waste or defective products. The purpose of "machine cleaning" is to remove these defective surface layers before entering the heating furnace and rolling mill to ensure the surface quality of the slab. However, extensive machine cleaning operations on the billet will lead to low metal yield and increased production costs.

[0085] This invention also provides a method for tracing the cause of abnormal liquid level fluctuations in the mold, including a method for discriminating abnormal liquid level fluctuations in the mold provided by this invention, and further includes the steps:​

[0086] S4: Based on the collected liquid level height in the crystallizer, calculate the liquid level fluctuation in the crystallizer, and then obtain multiple frequency bands corresponding to the liquid level fluctuation in the crystallizer using the discrete wavelet transform method. The frequency bands include frequency Rw and amplitude Ra information. When a peak value with amplitude Ra greater than ±3mm appears in the frequency band, it is judged as an abnormal fluctuation.

[0087] S5: Compare and analyze the casting parameters corresponding to the frequency of abnormal fluctuations in the liquid level of the crystallizer when slag entrapment occurs with the casting parameters corresponding to the frequency of normal liquid level fluctuations, establish rules for determining the causes of abnormal fluctuations in the liquid level of the crystallizer, and trace the causes of abnormal fluctuations in the liquid level.

[0088] It should be noted that this invention uses the discrete wavelet transform method to analyze the time-frequency characteristics of liquid level fluctuations in the crystallizer, enabling the tracing of the causes of abnormal liquid level fluctuations and 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 liquid level fluctuations and improving the quality of continuously cast billets, thereby reducing quality complaints and objections from users.

[0089] Specifically, in step S4, the calculation formula for the discrete wavelet transform analysis method is as follows:

[0090]

[0091] 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.

[0092] Specifically, in step S4, the wavelet basis function is selected as the Sym5 wavelet basis function; the maximum frequency after discrete wavelet transform is 5.0 Hz.

[0093] In step S4, the process parameters for slag entrapment on the crystallizer surface and normal casting include continuous casting billet production time, continuous casting billet width, crystallizer liquid level height, stopper rod position, casting speed, nozzle immersion depth, stopper rod argon flow rate, stopper rod argon back pressure, tundish top nozzle argon flow rate, tundish top nozzle argon back pressure, plate-to-plate argon flow rate, plate-to-plate argon back pressure, tundish tonnage, torque of the inner arc side drive rollers in different sector segments, and continuous casting billet reduction.

[0094] In step S5, based on the frequency and amplitude information corresponding to the fluctuation of the liquid surface in the crystallizer calculated by the discrete wavelet transform analysis method, the casting parameters corresponding to the abnormal fluctuation of the liquid surface in the crystallizer and the normal fluctuation conditions are compared to determine the rules for judging the cause of abnormal fluctuation of the liquid surface in the crystallizer.

[0095] In step S5, the specific rules for determining the cause of abnormal fluctuations in the mold liquid level are as follows:

[0096] When 0 < Rw < 0.1 Hz, the cause of abnormal liquid level fluctuations is a change in casting speed, continuous casting billet width, tundish tonnage, or submerged nozzle immersion depth;

[0097] When 0 < Rw < 0.1 Hz, if there is no change in casting speed, continuous casting billet width, or tundish tonnage, the cause of abnormal liquid level fluctuations 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 nozzle;

[0098] When 0.1 Hz ≤ Rw ≤ 0.4 Hz, the cause of abnormal liquid level fluctuations is unstable bulging between rolls;

[0099] When 0.4 Hz < Rw ≤ 1.0 Hz, the cause of abnormal liquid level fluctuations is severe nodulation of the stopper rod, tundish upper nozzle, or submerged nozzle;

[0100] When 1.0 Hz < Rw ≤ 5.0 Hz, the cause of abnormal liquid level fluctuations is the frequency, which is the natural frequency of mold vibration.

[0101] It should be noted that when 0 < Rw < 0.1 Hz, there are mainly two aspects to the cause of abnormal liquid level fluctuations. On the first hand, first check whether it is due to a change in casting speed, continuous casting billet 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 shedding of nodules that causes the fluctuation, which can be identified by whether there is a drastic change (jump) in the stopper rod position curve; then adjust, change, or clean the nodules on the tip or body of the stopper rod, the inner wall of the upper nozzle, or the submerged nozzle.

[0102] When 0.1 Hz ≤ Rw ≤ 0.4 Hz, the cause of abnormal liquid level fluctuations is unstable bulging between rolls. The occurrence of the bulging phenomenon can be identified based on the abnormal torque of the drive rolls on the inner arc side of different segment sectors and the abnormal reduction of the continuous casting billet. The static pressure generated by the molten steel in the continuous casting billet that has not been completely solidified inside exceeds the strength of the external solidified shell, resulting in the soft shell bulging outward and deforming, causing the bulging problem. By reducing the casting speed to increase the shell thickness and thus increase the strength, it is possible to better resist the static pressure of the internal molten steel, thereby reducing the risk of bulging. [[ID= twenty-two ]] [[ID= twenty-three ]]

[0103] When 0.4 Hz < Rw ≤ 1.0 Hz, the reason for the abnormal liquid level fluctuation is severe nodulation at the stopper rod, the upper nozzle of the tundish or the submerged entry nozzle. Whether the stopper rod is nodulated can be identified based on the abnormal argon flow rate and argon back pressure of the stopper rod. Whether the upper nozzle of the tundish is nodulated can be identified based on the abnormal argon flow rate and argon back pressure of the upper nozzle. Whether the submerged entry nozzle is nodulated can be identified based on the abnormal argon flow rate and argon back pressure between the plates. Adjust or control the above parameters to reduce the coefficient of nodulation.

[0104] When 1.0 Hz < Rw ≤ 5.0 Hz, this frequency is the natural characteristic frequency of the mold's own vibration, belonging to the natural fluctuation signal during the normal operation of the equipment, and 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 liquid level abnormality cause and process regulation, and no special treatment measures need to be taken for the frequencies in this interval.

[0105] To describe the present invention more clearly, it is further illustrated by the following examples and comparative examples.

[0106] Example 1

[0107] The process route for a certain steel plant to produce ultra-low carbon steel (C content is 0.0035%) is converter → RH refining furnace → continuous casting. The slab continuous casting machine is a one-machine two-strand arc caster, and the casting section of the mold is 1600 mm × 220 mm, with online width adjustment. An electromagnetic sensor is used to collect the liquid level fluctuation of the mold. The electromagnetic liquid level sensor is from VUHz Company in the Czech Republic, and the sensor model is SH7-S10, with a response time of 0.1 s. The sensor is installed on the outer arc side back plate of the mold, directly behind the submerged entry nozzle. The width of the measurement area is 800 mm, and the height of the measurement area is 100 mm downward from the upper edge of the mold along the casting direction. In this casting campaign, 9 heats of molten steel were continuously cast, and a total of 86 slabs were produced.

[0108] The sampling time of the production process data is 0.1 s, and the total casting duration is 32257.8 s. The calculation process is as follows:

[0109] (1) Taking ΔT = 0.1 s as the time step, T = 3.0 s as the time sliding window, and calculating the liquid level fluctuation index J of the mold for each continuous casting slab index and extracting the maximum value J of the liquid level fluctuation index max ;

[0110] (2) Counting the number of J index ≥ J slag for each continuous casting slab; determining the critical threshold of the liquid level fluctuation index corresponding to the occurrence of slag entrainment defect in the continuous casting slab, that is, the slag entrainment defect index J slag = 20 mm 2 / s.

[0111] (3) The model calculation results are judged by comparing the severity of slag entrapment in continuous casting billets and the judgment rules for pre-rolling billet treatment.

[0112] The predicted results of the slag entrapment degree of the continuously cast billet in this casting are shown in Table 1.

[0113] The number of hot-rolled slabs with slag inclusion defects in this casting batch is 45 (the actual number measured by the surface inspection system or surface inspection instrument). The model calculates that the number of continuous casting slabs with slag inclusion defects corresponding to the hot-rolled slabs is 43 (the number predicted by the identification method described in this invention is 11+12+20=43). Therefore, the accuracy rate of slag inclusion defect prediction is 43 / 45*100=95.6% (accuracy rate of slag inclusion defect prediction = number of slabs whose prediction results are consistent with the hot-rolled surface inspection results / total number of hot-rolled slag inclusion defects ×100).

[0114] Under the same casting parameters, since it was impossible to accurately determine abnormal fluctuations in the crystallizer liquid level, Comparative Example 1 used a crystallizer liquid level fluctuation exceeding ±5mm as the judgment criterion, predicting that the number of continuously cast billets with slag entrapment risk was 33, while the number of hot-rolled plates corresponding to this casting batch with slag entrapment defects was 50 (actually measured by a surface inspection system or surface inspection instrument). The accuracy rate of slag entrapment defect prediction in Comparative Example 1 was 33 / 50*100 = 66%.

[0115] Under the same casting parameters, since it is impossible to accurately determine abnormal fluctuations in the liquid level of the crystallizer, all continuous casting billets produced in Comparative Example 1 under the same casting parameters were cleaned by machine once, with a machine cleaning ratio of 100%.

[0116] Compared with Comparative Example 1, the number of machine-cleaned billets in Example 1 was 7, with a ratio of 7 / 86*100=8.1%. The proportion of machine-cleaned billets was reduced by 91.9%, which significantly improved the metal yield.

[0117] Table 1. Severity of slag contamination defects in continuously cast billets and pre-rolling billet treatment.

[0118]

[0119] Example 2

[0120] Example 2 is largely the same as Example 1 in its preparation process, except that in Example 2, the process for producing semi-peritectic steel (C content 0.091%) at a steel plant is as follows: converter → CAS refining furnace → continuous casting. The casting cross-section of the crystallizer is 1100mm × 230mm. The crystallizer liquid level acquisition frequency is 10Hz. This casting run involves 10 heats of molten steel, producing a total of 80 billets.

[0121] The sampling time for the production process data was 0.1s, and the total casting time was 34587.5s.

[0122] Using a time step of ΔT = 0.1 s and a time sliding window of T = 3.0 s, the maximum values ​​of the crystallizer liquid level fluctuation index and the extraction liquid level fluctuation index were calculated for each continuously cast billet. Based on the severity of slag contamination defects in the billets and the judgment rules for pre-rolling billet treatment, the corresponding machine cleaning operations for continuously cast billets under different degrees of slag contamination are shown in Table 2. The number of hot-rolled plates with slag contamination defects in this casting batch was 30 coils (actually measured by a surface inspection system or instrument). The predicted number of slag-contaminated billets corresponding to the hot-rolled plates with slag contamination defects was 29 coils. Therefore, the accuracy rate of slag contamination defect prediction was 29 / 30*100 = 96.7%.

[0123] Under the same casting parameters, since it was impossible to accurately determine abnormal fluctuations in the crystallizer liquid level, Comparative Example 2 used a crystallizer liquid level fluctuation exceeding ±5mm as the judgment criterion, predicting that the number of continuously cast billets with slag entrapment risk was 20, while the number of hot-rolled plates corresponding to this casting batch with slag entrapment defects was 33 (actually measured by a surface inspection system or surface inspection instrument). The accuracy rate of slag entrapment defect prediction in Comparative Example 2 was 20 / 33*100 = 60.6%.

[0124] Under the same casting parameters, since it was impossible to accurately determine abnormal fluctuations in the liquid level of the crystallizer, all continuous casting billets produced in Comparative Example 2 under the same casting parameters were cleaned by machine once, with a machine cleaning ratio of 100%.

[0125] Compared with Comparative Example 2, the number of machine-cleaned billets in Example 2 was 12, and the proportion was 12 / 80*100=15%. The proportion of machine-cleaned billets was reduced by 85%, which greatly improved the metal yield.

[0126] Table 2 Severity of Slag Injection Defects in Continuously Cast Billets and Pre-Rolling Billet Treatment

[0127]

[0128] Application Example 1

[0129] Application Example 1 is an application example corresponding to Example 1.

[0130] The continuous casting billet width is 1600mm; the casting speed is 1.4m / min; the tundish nozzle immersion depth is 160mm; the stopper rod argon flow rate is 3NL / min, and the stopper rod argon back pressure is 0.55bar; the tundish top nozzle argon flow rate is 3NL / min, and the tundish top nozzle argon back pressure is 0.66bar; the inter-plate argon flow rate is 10NL / min, and the inter-plate argon back pressure is 0.58bar; the ladle tonnage is 320t, and the tundish tonnage is... The casting depth is 70t; the torques of the drive rollers on the inner arc side of sector sections 1 to 11 are 33.4, 31.2, 30.6, 35.0, 35.9, 34.0, 38.8, 36.2, 28.6, 34.6, and 36.8 N·m, respectively; the reduction of the continuously cast billet is 0.30, 0.30, 0.31, 0.33, 0.31, 0.30, 0.32, 0.32, 0.35, 0.34, and 0.35 mm, respectively. The superheat of the tundish is 24℃. The cooling water flow rate of the narrow face of the crystallizer is 520 NL / min, the cooling water flow rate of the wide face is 4650 NL / min, and the secondary cooling water flow rate of the crystallizer is 350 NL / min.

[0131] Discrete wavelet transform was used to analyze and determine the crystallizer level height when slag entrapment occurred and the crystallizer level height under normal casting conditions, as well as the corresponding process parameters. The causes of abnormal crystallizer level fluctuations during this casting process included changes in the tonnage of the tundish during ladle replacement and blockage of the submerged entry nozzle (see Table 3). Stable control of crystallizer level fluctuations was achieved by timely adjustment of process parameters. In contrast, Comparative Example 1 used a crystallizer level fluctuation exceeding ±5mm as the criterion, which could not accurately determine the abnormal crystallizer level fluctuations and their causes.

[0132] Table 3. Judgment of Abnormal Fluctuations in Crystallizer Liquid Level, Tracing of Abnormal Causes, and Optimization of Process Parameters

[0133]

[0134] Application Example 2

[0135] Application Example 2 corresponds to the application example of Example 2.

[0136] The continuous casting billet width is 1100mm; the casting speed is 1.5m / min; the tundish nozzle immersion depth is 140mm; the stopper rod argon flow rate is 4NL / min, and the stopper rod argon back pressure is 0.41bar; the tundish top nozzle argon flow rate is 4NL / min, and the tundish top nozzle argon back pressure is 0.35bar; the interplate argon flow rate is 10NL / min, and the interplate argon back pressure is 0.36bar; the ladle tonnage is 320t, and the tundish tonnage is 70t; The torques of the drive rollers on the inner arc side of sections 1 to 11 are 19.3, 22.4, 19.6, 20.0, 21.0, 22.9, 28.6, 19.7, 18.1, 15.6, and 14.8 N·m, respectively; the reduction of the continuously cast billet is 0.30 mm, 0.30 mm, 0.30 mm, 0.32 mm, 0.30 mm, 0.30 mm, 0.31 mm, 0.31 mm, 1.39 mm, and 1.38 mm, respectively. The superheat of the tundish is 28℃. The cooling water flow rate of the narrow face of the crystallizer is 460 NL / min, the cooling water flow rate of the wide face is 3200 NL / min, and the secondary cooling water flow rate of the crystallizer is 340 NL / min.

[0137] Discrete wavelet transform was used to analyze and determine the crystallizer level height when slag entrapment occurred and the crystallizer level height under normal casting conditions, as well as the corresponding process parameters. The cause of the abnormal fluctuation in the crystallizer level during this casting process was a bulging phenomenon in the continuous casting machine (see Table 4), and the crystallizer level fluctuation was stabilized by timely adjustment of process parameters. In contrast, Comparative Example 2 used a crystallizer level fluctuation exceeding ±5mm as the judgment criterion, which could not accurately determine the abnormal fluctuation in the crystallizer level and its cause.

[0138] Table 4. Judgment of Abnormal Fluctuations in Crystallizer Liquid Level, Tracing of Abnormal Causes, and Optimization of Process Parameters

[0139]

[0140] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying abnormal fluctuations in the liquid level of a crystallizer, characterized in that, Includes the following steps: S1: Collect continuous casting production data and calculate the crystallizer liquid level fluctuation index; S2: Compare and analyze the maximum value of the crystallizer liquid level fluctuation index calculated for each continuous casting billet, and the judgment result of the corresponding slag entrapment defect on the hot-rolled plate, so as to determine the critical threshold of the liquid level fluctuation index corresponding to the occurrence of slag entrapment defect in the continuous casting billet, i.e., the slag entrapment defect index. S3: Count the number of crystallizer liquid level fluctuation indices that are greater than or equal to the slag entrapment defect index on each continuous casting billet, and compare and analyze the number of slag entrapment defects on the corresponding hot-rolled plate to establish a judgment rule for the severity of slag entrapment on the continuous casting billet.

2. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, In step S1, the continuous casting production data includes the continuous casting billet production time, continuous casting billet width, crystallizer liquid level height, stopper rod position, casting speed, tundish tonnage, torque of the inner arc side drive rollers in different sector segments, and continuous casting billet reduction. The above process parameters are matched with the billet number, casting machine flow number, furnace number, and steel grade, based on the billet production time, using the continuous casting billet as the unit.

3. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, In step S1, the crystallizer liquid level fluctuation index = the maximum slope of the crystallizer liquid level multiplied by the maximum amplitude of the crystallizer liquid level, J 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.

4. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 3, characterized in that, The formula for calculating the slope of the crystallizer liquid level is: 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.

5. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 3, characterized in that, 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 ).

6. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 3, characterized in that, In step S1, the maximum amplitude of the crystallizer liquid level is calculated as follows: using T as the time sliding window and ΔT as the sliding time step, the maximum value L of the liquid level within the time interval T is found. max =max(L1, L2…L) n The minimum 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 ; In the formula, L max L represents the maximum liquid level within time interval T, in mm. min The minimum liquid level within time interval T, in mm.

7. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, For each continuously cast billet, extract the maximum value J of the liquid level fluctuation index during the billet production time. max ; J max =max(J1,J2...J n ) Extract the number of slag contamination defects in a slab whose liquid level fluctuation index is greater than or equal to the slag contamination defect index during the production time of the slab. 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.

8. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, The value of the slag entanglement defect index for the corresponding hot-rolled plate used to determine whether the continuously cast billet exhibits slag entanglement defects is J. slag =20~40mm 2 / s.

9. The method for judging abnormal fluctuations in crystallizer liquid level according to claim 1, characterized in that, Rules for determining the severity of slag contamination in continuously cast billets: 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 and when N < 5, it is determined as mild slag entrainment and the machine is cleaned 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 the machine is cleaned once; 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 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 determined as severe slag entrainment and the machine is cleaned once; When J slag +50 mm 2 / s < J max , and when 15 < N, it is determined as severe slag entrainment, and the machine is cleaned twice.

10. A method for tracing the cause of abnormal liquid level fluctuations, characterized in that, The method for identifying abnormal fluctuations in crystallizer liquid level, as described in any one of claims 1-9, combines the method for identifying abnormal fluctuations in crystallizer liquid level with the rules for determining the causes of abnormal fluctuations in crystallizer liquid surface to trace the source of abnormal fluctuations in liquid surface.

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