Method and system for identifying breakout of a continuous casting mold

Abstract

The application provides a continuous casting machine crystallizer breakout identification method and system, which obtains the thermal electric couple data of the crystallizer, the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in a set time interval before the bonding feature change moment, determines the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval, determines that the crystallizer of the continuous casting machine is in a first state when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, determines that the crystallizer of the continuous casting machine is in a second state when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, and determines that the crystallizer of the continuous casting machine is in a third state when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value. The application finally achieves the technical effect of greatly reducing the false alarm rate in the non-steady state continuous casting production scene.

Description

Technical Field

[0001] This invention relates to the field of continuous casting machine technology, and more specifically, to a method and system for identifying steel leakage in the crystallizer of a continuous casting machine. Background Technology

[0002] In continuous casting, if the solidified shell formed in the crystallizer ruptures for some reason, and the rupture cannot be reformed and repaired before the section of the cast billet is pulled out of the crystallizer, an accident occurs where the molten steel in the crystallizer and the billet suddenly leaks out. This accident is called a breakout. Breakouts are one of the most serious accidents in continuous casting production, causing direct economic losses and disrupting the orderly production process. Monitoring crystallizer breakouts is a crucial aspect of steel production and can be achieved through several monitoring technologies: thermocouple-based temperature monitoring, friction-based monitoring, and heat flow analysis-based monitoring. Among these, thermocouple-based temperature monitoring is currently the most commonly used and effective method for predicting breakouts due to its high accuracy and reliability. Thermocouple-based temperature monitoring involves embedding a certain number of thermocouples within the copper plate of the crystallizer to monitor temperature changes in real time. When a breakout occurs, the molten steel comes into direct contact with the copper plate, causing a sharp rise in the temperature of the thermocouples at the corresponding locations. By monitoring this temperature change, a breakout can be predicted. In steady-state production processes, the accuracy of steel leakage prediction based on thermocouple temperature monitoring methods is relatively high.

[0003] However, because the temperature change characteristics inside the crystallizer during unsteady-state production are somewhat similar to those during steel leakage, the system has difficulty in accurately distinguishing them; consequently, the traditional steel leakage prediction system has a high false alarm rate under unsteady-state production conditions.

[0004] Therefore, there is an urgent need for a method to identify steel leakage in the crystallizer of a continuous casting machine suitable for non-steady-state production. Summary of the Invention

[0005] In view of the above problems, the purpose of this invention is to provide a method and system for identifying steel leakage in a continuous casting machine crystallizer, so as to solve at least one problem existing in the prior art.

[0006] According to one aspect of the present invention, a method for identifying steel leakage in a continuous casting machine crystallizer is provided, applied to electronic equipment, comprising:

[0007] Acquire thermocouple data from the crystallizer and determine the timing of changes in adhesion characteristics based on the thermocouple data from the crystallizer;

[0008] Acquire the continuous casting machine casting speed data and continuous casting machine crystallizer liquid level data within a set time interval before the moment of change of the bonding characteristics;

[0009] According to the acquired continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data, the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval is determined;

[0010] According to the standard deviation, the state of the crystallizer of the continuous casting machine is determined; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state;

[0011] When the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state;

[0012] When the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state.

[0013] In addition, the optional technical solution further comprises,

[0014] The first state is a stable operation state of the continuous casting machine;

[0015] The second state is a sub-stable operation state of the continuous casting machine;

[0016] The third state is an abnormal operation state of the continuous casting machine.

[0017] In addition, the optional technical solution further comprises,

[0018] When it is determined that the crystallizer of the continuous casting machine is in the first state, the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the continuous casting machine pulling speed data are acquired;

[0019] According to the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the minimum rising temperature of the upper thermocouple temperature is acquired, and according to the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the minimum rising temperature of the lower thermocouple temperature is acquired; according to the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple, the moving speed of the high temperature point time between the two thermocouples is acquired; and then according to the moving speed of the high temperature point time between the two thermocouples and the continuous casting machine pulling speed data, the ratio of the moving speed of the high temperature point time between the two thermocouples to the pulling speed is determined;

[0020] The mold state is monitored according to the first rule; if the minimum temperature rise of the upper thermocouple or the minimum temperature rise of the lower thermocouple and the ratio of the speed of the high temperature point moving between the two thermocouples to the casting speed meet the first rule, a breakout alarm signal is sent.

[0021] In addition, the optional technical solution further comprises,

[0022] When it is determined that the mold of the continuous casting machine is in the second state, the initial temperature and the maximum temperature of the upper thermocouple when the temperature rise curve appears, the initial temperature and the maximum temperature of the lower thermocouple when the temperature rise curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the casting speed data of the continuous casting machine are obtained.

[0023] The minimum temperature rise of the upper thermocouple is obtained according to the initial temperature and the maximum temperature of the upper thermocouple when the temperature rise curve appears, and the minimum temperature rise of the lower thermocouple is obtained according to the initial temperature and the maximum temperature of the lower thermocouple when the temperature rise curve appears; the speed of the high temperature point moving between the two thermocouples is obtained according to the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple; and then the ratio of the speed of the high temperature point moving between the two thermocouples to the casting speed is determined according to the speed of the high temperature point moving between the two thermocouples and the casting speed data of the continuous casting machine.

[0024] The mold state is monitored according to the second rule; if the minimum temperature rise of the upper thermocouple or the minimum temperature rise of the lower thermocouple and the ratio of the speed of the high temperature point moving between the two thermocouples to the casting speed meet the second rule, a breakout alarm signal is sent.

[0025] In addition, the optional technical solution further comprises,

[0026] When it is determined that the mold of the continuous casting machine is in the third state, the casting speed data, the mold level data of the continuous casting machine, and the mold vibration data are obtained.

[0027] The abnormal state type of the continuous casting machine is determined according to the obtained casting speed data, the mold level data of the continuous casting machine, and the mold vibration data.

[0028] In addition, the optional technical solution further comprises,

[0029] The abnormal state type of the continuous casting machine includes any one of the water nozzle state of the continuous casting machine, the intermediate ladle state, the abnormal accident state, the casting start-up speed-up state, the casting stop state, the casting speed-up state, and the casting speed-down state.

[0030] In addition, the optional technical solution further comprises,

[0031] After determining the abnormal state type of the continuous casting machine according to the acquired continuous casting machine pulling speed data, continuous casting machine crystallizer liquid level data and crystallizer vibration data, the method further comprises:

[0032] According to the abnormal state type of the continuous casting machine, the breakout monitoring is performed according to the determination rule corresponding to the abnormal state type of the continuous casting machine.

[0033] On the other hand, the present application also provides a continuous casting machine crystallizer breakout identification system, which uses the continuous casting machine crystallizer breakout identification method as described above to identify the breakout; the system comprises:

[0034] A data acquisition unit is configured to acquire the crystallizer thermocouple data, and determine the sticking feature change time according to the crystallizer thermocouple data; acquire the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data within a set time interval before the sticking feature change time;

[0035] A data processing unit is configured to determine the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data within the set time interval according to the acquired continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data;

[0036] A state determination unit is configured to determine the state of the crystallizer of the continuous casting machine according to the standard deviation; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state;

[0037] When the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state;

[0038] When the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state.

[0039] The continuous casting machine crystallizer breakout identification method and system, by acquiring the crystallizer thermocouple data, and determining the sticking feature change moment according to the crystallizer thermocouple data; acquiring the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval before the sticking feature change moment; determining the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval according to the acquired continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than the first threshold value, it is determined that the crystallizer of the continuous casting machine is in the first state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in the second state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in the third state. The present application ultimately achieves the technical effect of greatly reducing the false alarm rate in the non-steady state continuous casting production scene.

[0040] To the accomplishment of the foregoing and related ends, one or more aspects of the application comprise the features hereinafter fully described and particularly pointed out in the claims. The following description and the annexed drawings set forth in detail certain illustrative aspects of the application. These aspects are indicative, however, of but a few of the various ways in which the principles of the application can be employed. Other objects, advantages, and novel features of the application will become apparent from the following detailed description when considered in conjunction with the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0041] Other objects and advantages of the application will become apparent upon reading the following detailed description and upon examining the drawings, in which:

[0042] Figure 1 A flowchart of a continuous casting machine crystallizer breakout identification method according to an embodiment of the application;

[0043] Figure 2 A continuous casting machine crystallizer liquid level data example according to an embodiment of the application;

[0044] Figure 3 A module schematic diagram of a continuous casting machine crystallizer breakout identification system provided by an embodiment of the application.

[0045] Figure 4 An internal structure schematic diagram of an electronic device for implementing a continuous casting machine crystallizer breakout identification method provided by an embodiment of the application.

[0046] The same reference numbers in all the drawings indicate similar or corresponding features or functions. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0048] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings. In the description of the embodiments of the present application, "and / or" in the text only represents an association relationship of associated objects, and represents that there can be three relationships, for example, A and / or B can represent that there are three cases of A alone, A and B together, and B alone.

[0049] Hereinafter, the terms "first" and "second" are only for description purposes, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in addition, "multiple" in the description of the embodiments of the present application means two or more than two.

[0050] In the present specification, the reference "one embodiment" or "some embodiments" and the like means that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Therefore, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in yet some embodiments" and the like appearing in different places in the present specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "include", "contain", "have" and their variants mean "including but not limited to", unless otherwise specifically emphasized.

[0051] In order to describe the continuous casting machine crystallizer breakout recognition method and system in detail, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0052] AI is the theory, method, technology and application system of simulating, extending and expanding human intelligence by using digital computers or machines controlled by digital computers, perceiving the environment, acquiring knowledge and using knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology of computer science, which tries to understand the essence of intelligence and produce a new intelligent machine that can react in a similar way to human intelligence. Artificial intelligence is the design principle and implementation method of various intelligent machines, so that machines have the functions of perception, reasoning and decision-making. Artificial intelligence technology is a comprehensive discipline, involving a wide range of fields, both hardware and software technologies. Artificial intelligence basic technologies generally include sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction system, mechatronics and other technologies. Artificial intelligence software technology mainly includes computer vision technology, speech processing technology, natural language processing technology and machine learning / deep learning and other major directions.

[0053] Machine learning (ML) is a multi-disciplinary subject, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It is a specialized study of how computers simulate or implement human learning behavior to acquire new knowledge or skills, reorganize existing knowledge structure to continuously improve their performance. Machine learning is the core of artificial intelligence and the fundamental approach to making computers intelligent, and its applications are widespread in various fields of artificial intelligence. Machine learning and deep learning usually include artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and rule-based learning.

[0054] Figure 1 A continuous casting machine crystallizer breakout identification method flow chart according to an embodiment of the application is shown.

[0055] As shown in Figure 1 The continuous casting machine crystallizer breakout identification method provided by the embodiment is applied to an electronic device and mainly includes the following steps:

[0056] S110: Obtain the crystallizer thermocouple data and determine the sticking feature change time according to the crystallizer thermocouple data. S120: Obtain the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in a set time interval before the sticking feature change time.

[0057] It should be noted that the crystallizer is the core component of the continuous casting machine, and its intelligent control is crucial to the quality of the casting blank. In the specific implementation process, accurate monitoring of the crystallizer thermocouple data, crystallizer liquid level fluctuation, local heat flow dynamic change, actual blank shell "hot spot" tracking, etc. can be realized. The thermocouple is correctly installed on the crystallizer copper plate, ensuring that the thermocouple is in good contact with the copper plate, avoiding oil stains, loose bolts, loose joints and other problems, to ensure the accuracy of the collected temperature data. Real-time collection of temperature data of the crystallizer thermocouple. Real-time analysis of the temperature data collected by the crystallizer thermocouple, when abnormal fluctuations or preset alarm thresholds are detected, it can be judged as the moment of adhesion characteristic change.

[0058] In a specific embodiment, the thermocouples arranged in the continuous casting crystallizer copper plate are arranged in 3 to 6 rows, and the number of columns of thermocouples for each copper plate is 6-20, which is specifically arranged according to the actual size of the copper plate. Each interval of 133mm needs to arrange a column of thermocouples. For two adjacent upper and lower thermocouples, here UTCT refers to the upper thermocouple, and DTCT refers to the lower thermocouple. The basic temperature value, temperature rise slope, temperature drop slope, highest temperature point moment, and the physical distance between the highest temperature point moment and the upper and lower thermocouples of the upper and lower thermocouples are all data collection objects.

[0059] In the specific implementation process, the acquired crystallizer thermocouple data can be determined to determine the adhesion feature change moment through a supervised learning model, an unsupervised learning model, a time series analysis model, and the like. The machine learning model is a mathematical structure or algorithm that can learn and infer useful information from input data, and then make predictions or decisions on new data. In the field of machine learning, the model is established by training on existing data, and this training process involves optimizing the model parameters to best fit the training data and is expected to have good generalization ability on unknown data. For example, an artificial neural network (ANN): ANN can learn the complex nonlinear relationship between input features (thermocouple data) and output labels (adhesion feature change moment) through training, and has good prediction ability and generalization ability. Random forest is composed of multiple decision trees, and the prediction results of multiple models are integrated to improve the prediction accuracy and stability. Clustering algorithms such as K-means, hierarchical clustering, etc. can be used to cluster the thermocouple data, and the data is divided into different clusters, and then the features of each cluster are analyzed to identify the adhesion feature change moment. Long short-term memory network (LSTM): LSTM is a special recurrent neural network that can capture long-term dependencies in time series data, suitable for modeling and predicting the time series of thermocouple data. In addition, data preprocessing (such as denoising, normalization, etc.) and selection of appropriate feature engineering methods are also needed to extract key features that help the model make predictions. Through training and testing the model, the model parameters are constantly optimized, and finally the adhesion feature change moment in the crystallizer thermocouple data is accurately determined.

[0060] S130: According to the acquired continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data, the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval is determined.

[0061] The standard deviation is a statistical measure of the dispersion of a set of data, which represents the average distance between the data points and the mean value. Specifically, the mean value needs to be calculated first, then the square of the difference between each data point and the mean value is calculated, and then the average of these squared differences is calculated, that is, the variance. Finally, take the square root of the variance, that is, the standard deviation. In the prior art, the liquid level fluctuation of the continuous casting machine is taken as the only indicator for judging the breakout. However, the present application takes the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data as the preconditions for judging the breakout according to the temperature, further improving the accuracy of the breakout identification.

[0062] The set time interval can be 40-150 seconds. According to the specific application scenario, no specific limitation is made.

[0063] S140: Determine the state of the continuous casting machine's crystallizer based on the standard deviation; wherein, when the standard deviation of the continuous casting machine's casting speed data and the continuous casting machine's crystallizer level data is less than a first threshold, the continuous casting machine's crystallizer is determined to be in a first state; when the standard deviation of the continuous casting machine's casting speed data and the continuous casting machine's crystallizer level data is greater than the first threshold and less than a second threshold, the continuous casting machine's crystallizer is determined to be in a second state; when the standard deviation of the continuous casting machine's casting speed data and the continuous casting machine's crystallizer level data is greater than the second threshold, the continuous casting machine's crystallizer is determined to be in a third state. The first state is the continuous casting machine's stable operation state; the second state is the continuous casting machine's sub-stable operation state; and the third state is the continuous casting machine's abnormal operation state.

[0064] Specifically, such as Figure 2 As shown, the data of the crystallizer thermocouple, the continuous casting machine speed, and the continuous casting machine crystallizer liquid level are combined and analyzed on the same time axis. When the thermocouple temperature exhibits a sticking characteristic change, the fluctuations in the continuous casting machine's casting speed and liquid level within the preceding 60 seconds are statistically analyzed. If the combined standard deviation of the casting speed and liquid level within this time range is 5%, the system is considered to be within the normal steady-state operating range, and real-time judgment calculations are performed according to the relevant methods of the standard leakage prediction characteristic curve. When the combined standard deviation of the casting speed and liquid level within this time range is between 5% and 15%, the system is considered to be in a steady-state but unstable operating state, and real-time judgment calculations are performed according to the second set of leakage prediction identification algorithm standards. When the combined standard deviation of the casting speed and liquid level within this time range is greater than 15%, the current casting machine state is considered to be in an unsteady state. At this time, the production status of the continuous casting machine is comprehensively evaluated through relevant signals such as casting speed, liquid level, and crystallizer vibration, specifically divided into continuous casting machine nozzle change state, tundish change state, abnormal accident state, casting start and speed increase state, casting stop state, speed increase state, and speed decrease state.

[0065] In a specific implementation process, the determination of the continuous casting machine state can be realized by a neural network model, a support vector machine model, etc. For example, a BP neural network model is used, the casting speed data, the liquid level data, and their standard deviations are taken as network inputs, the model is trained to identify the mold state and the breakout signs. When the model determines that the mold is in the first state, a breakout alarm is triggered. The support vector machine model: a multi-class support vector machine model is used to classify the continuous casting machine state information, and the warning level is set according to the classification result. When the mold is in the first state, a breakout alarm is issued. Specifically, a large amount of continuous casting machine operation data is collected, including normal state and breakout accident data. The data is labeled to form a training data set. The neural network and support vector machine model are trained using the training data set, and the model parameters are adjusted to accurately identify the mold state and breakout signs. The performance of the model is evaluated by cross-validation and other methods, and the model is optimized according to the evaluation results to reduce the false negative rate and the false positive rate. The trained model is deployed in the real-time monitoring system to receive the casting speed data and the liquid level data of the continuous casting machine in real time, calculate the standard deviation, and determine the state. When the model determines that the mold is in the first state, a breakout alarm is automatically triggered to remind the operator to take appropriate measures, such as adjusting the casting speed, increasing the negative strip time, etc., to avoid the occurrence of breakout accidents.

[0066] In a specific embodiment, when it is determined that the mold of the continuous casting machine is in the first state, the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the casting speed data of the continuous casting machine are obtained; the minimum temperature rising temperature of the upper thermocouple is obtained according to the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, and the minimum temperature rising temperature of the lower thermocouple is obtained according to the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears; the moving speed of the high temperature point time between the two thermocouples is obtained according to the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple; then the ratio of the moving speed of the high temperature point time between the two thermocouples to the casting speed is determined according to the moving speed of the high temperature point time between the two thermocouples and the casting speed data; the mold state is monitored according to the first rule; if the minimum temperature rising temperature of the upper thermocouple or the minimum temperature rising temperature of the lower thermocouple and the ratio of the moving speed of the high temperature point time between the two thermocouples to the casting speed meet the first rule, a breakout alarm signal is issued. For example, the first rule is that the minimum temperature rising temperature of the corresponding upper and lower thermocouples is set to 4 degrees in the steady state, and the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is 0.1-3.0, and there is no need to make the same judgment on the left and right two rows of thermocouples.

[0067] When it is determined that the crystallizer of the continuous casting machine is in the second state, the initial temperature and the highest temperature of the upper thermocouple when the temperature rising curve appears, the initial temperature and the highest temperature of the lower thermocouple when the temperature rising curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the casting speed data of the continuous casting machine are obtained; the minimum temperature rising temperature of the upper thermocouple is obtained according to the initial temperature and the highest temperature of the upper thermocouple when the temperature rising curve appears, and the minimum temperature rising temperature of the lower thermocouple is obtained according to the initial temperature and the highest temperature of the lower thermocouple when the temperature rising curve appears; the moving speed of the high temperature point between the two thermocouples at the high temperature point time is obtained according to the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple; then the ratio of the moving speed of the high temperature point between the two thermocouples at the high temperature point time to the casting speed is determined according to the moving speed of the high temperature point between the two thermocouples at the high temperature point time and the casting speed data of the continuous casting machine; the crystallizer state monitoring is performed according to the second rule; if the minimum temperature rising temperature of the upper thermocouple or the minimum temperature rising temperature of the lower thermocouple and the ratio of the moving speed of the high temperature point between the two thermocouples at the high temperature point time to the casting speed meet the second rule, a breakout alarm signal is sent. For example, the second rule is that, since in a relatively unstable state, the breakout prediction rule needs to be further limited and requires to be more stringent, the minimum temperature rising temperature of the upper and lower thermocouples is set to 6 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is 0.5-2.5, and the same judgment needs to be made for the left and right two thermocouples.

[0068] When it is determined that the crystallizer of the continuous casting machine is in the third state, the casting speed data, the crystallizer liquid level data and the crystallizer vibration data of the continuous casting machine are obtained; the abnormal state type of the continuous casting machine is determined according to the obtained casting speed data, the crystallizer liquid level data and the crystallizer vibration data.

[0069] The abnormal state type of the continuous casting machine includes any one of the water nozzle state of the continuous casting machine, the intermediate ladle state, the abnormal accident state, the casting start-up speed increasing state, the casting stop state, the casting speed increasing state and the casting speed decreasing state.

[0070] After determining the abnormal state type of the continuous casting machine according to the obtained casting speed data, the crystallizer liquid level data and the crystallizer vibration data, the breakout monitoring is performed according to the determination rule corresponding to the abnormal state type of the continuous casting machine.

[0071] For example, due to the more unstable state, further limitation is needed for the breakout prediction rule. The corresponding third rule under the water nozzle working condition sets the minimum temperature rise of the upper and lower thermocouples to 7 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is between 0.6 and 2.0, and the same judgment needs to be made for the left and right two rows of thermocouples. For example, the criteria for determining the water nozzle change of the continuous casting machine is that the casting speed of the continuous casting machine is reduced within 8 minutes, and the rate of speed reduction is more than 0.3 m / min. The casting speed is reduced by more than 0.3 m / min, and the reduced casting speed is maintained for more than 30 seconds, and the standard deviation of the liquid level fluctuation during this period is less than 10%. It is determined to be a breakout, and a breakout alarm is given.

[0072] Due to the more unstable state, further limitation is needed for the breakout prediction rule. The corresponding fourth rule under the tundish working condition sets the minimum temperature rise of the upper and lower thermocouples to 8 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is between 0.8 and 1.9, and the same judgment needs to be made for the left and right two rows of thermocouples. For example, the casting speed of the continuous casting machine is reduced to 0 m / min, and the difference between the liquid level data and the production time is less than 10%, and it is determined to be a breakout, and a breakout alarm is given.

[0073] Due to the more unstable state, further limitation is needed for the breakout prediction rule. The corresponding fifth rule under the accident working condition sets the minimum temperature rise of the upper and lower thermocouples to 8 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is between 0.8 and 1.5, and the same judgment needs to be made for the left and right two rows of thermocouples. For example, the standard deviation of the mold level fluctuation is greater than 80% within 5 seconds, and the absolute value of the single temperature rise or temperature drop of the mold water temperature is greater than 1 degree, and it is determined to be a breakout, and a breakout alarm is given.

[0074] Due to the more unstable state, further limitation is needed for the breakout prediction rule. The corresponding sixth rule under the starting working condition sets the minimum temperature rise of the upper and lower thermocouples to 9 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is between 0.8 and 1.4, and the same judgment needs to be made for the left and right two rows of thermocouples. For example, the mold level continues to rise and the casting speed of the continuous casting machine gradually increases from 0 to the production casting speed, and it is determined to be a breakout, and a breakout alarm is given.

[0075] Due to the more unstable state, further limitation is needed for the breakout prediction rule. The corresponding seventh rule under the stop working condition sets the minimum temperature rise of the upper and lower thermocouples to 9 degrees, the ratio of the moving speed of the high temperature point between the two thermocouples to the casting speed is between 0.8 and 1.2, and the same judgment needs to be made for the left and right two rows of thermocouples. For example, the mold level continues to decrease and the casting speed of the continuous casting machine gradually decreases from the production casting speed to below 0.5, and it is determined to be a breakout, and a breakout alarm is given.

[0076] Due to the more unstable state, the breakout prediction rule needs to be further limited. The eighth rule corresponding to the rising speed corresponds to the minimum temperature rise of the upper and lower thermocouple temperatures of 6 degrees, the moving speed of the high temperature point between the two thermocouples is 0.5-1.5 times the pulling speed, and the same judgment needs to be made on the left and right two thermocouples. For example, the pulling speed change trend is consistent, the absolute value of the change per minute is >0.05 m / min, and the standard deviation of the mold level is <5%, which is determined as a breakout, and a breakout alarm is performed.

[0077] Due to the more unstable state, the breakout prediction rule needs to be further limited. The ninth rule corresponding to the falling speed corresponds to the minimum temperature rise of the upper and lower thermocouple temperatures of 8 degrees, the moving speed of the high temperature point between the two thermocouples is 0.5-1.5 times the pulling speed, and the same judgment needs to be made on the left and right two thermocouples. For example, the pulling speed change trend is consistent, the absolute value of the change per minute is >0.05 m / min, and the standard deviation of the mold level is <5%, which is determined as a breakout, and a breakout alarm is performed.

[0078] The first threshold is 5%, and the second threshold is 15%. In the specific implementation process, the indexes marked with 5% and 15% in the entire control strategy can be freely adjusted according to the actual situation of different production sites. No specific limitation is made here.

[0079] As shown in Figure 3 The present application provides a continuous casting mold breakout identification system, which uses the continuous casting mold breakout identification method as described above for voice recognition. According to the realized function, the continuous casting mold breakout identification system 200 can include a data acquisition unit 210, a data processing unit 220, and a state determination unit 230. The units of the present application can also be referred to as modules, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete a fixed function, which are stored in the memory of the electronic device.

[0080] In this embodiment, the functions of each module / unit are as follows:

[0081] The data acquisition unit 210 is used to acquire the mold thermocouple data and determine the sticking feature change time according to the mold thermocouple data; acquire the continuous casting machine pulling speed data and the continuous casting machine mold level data within a set time interval before the sticking feature change time;

[0082] The data processing unit 220 is used to determine the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine mold level data within the set time interval according to the acquired continuous casting machine pulling speed data and the continuous casting machine mold level data;

[0083] The state determination unit 230 is configured to determine the state of the crystallizer of the continuous casting machine according to the standard deviation; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state;

[0084] When the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state;

[0085] When the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state.

[0086] The continuous casting machine crystallizer breakout identification system of the present application acquires the crystallizer thermocouple data, and determines the sticking feature change time according to the crystallizer thermocouple data; acquires the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data in a set time interval before the sticking feature change time; determines the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data in the set time interval according to the acquired continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state. The present application ultimately achieves the technical effect of greatly reducing the false alarm rate in the non-steady state continuous casting production scenario.

[0087] The more specific implementation modes of the above-mentioned continuous casting machine crystallizer breakout identification system can be referred to the description of the embodiments of the continuous casting machine crystallizer breakout identification method, which will not be described in detail here.

[0088] As shown in the figure, Figure 4 The present application also provides an electronic device 1 for the continuous casting machine crystallizer breakout identification method.

[0089] The electronic device 1 can include a processor 10, a memory 11 and a bus, and can also include a computer program stored in the memory 11 and executable on the processor 10, such as a continuous casting machine crystallizer breakout identification program 12. The memory 11 can also include both an internal storage unit of the continuous casting machine crystallizer breakout identification system and an external storage device. The memory 11 can be used not only to store installed application software and various data, such as the code of the continuous casting machine crystallizer breakout identification program, but also to temporarily store data that has been output or will be output.

[0090] The electronic device 1 can include a processor 10, a memory 11 and a bus, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as a continuous casting mold breakout identification program 12. The memory 11 can include both an internal storage unit and an external storage device of the continuous casting mold breakout identification system. The memory 11 can be used not only to store installed application software and various data, such as the code of the continuous casting mold breakout identification program, but also to temporarily store data that has been output or will be output.

[0091] The memory 11 includes at least one type of readable storage medium, such as a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 11 can include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 can be used not only to store installed application software and various data, such as the code of the continuous casting mold breakout identification program, but also to temporarily store data that has been output or will be output.

[0092] The processor 10 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of a central processing unit (CPU), a microprocessor, a digital processing chip, a graphics processor and various control chips, etc. The processor 10 is the control unit of the electronic device, which connects various components of the entire electronic device through various interfaces and lines, executes programs or modules stored in the memory 11 (such as the continuous casting mold breakout identification program), and calls data stored in the memory 11 to perform various functions and process data of the electronic device 1.

[0093] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11, the at least one processor 10, etc.

[0094] Figure 4 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 4 The structure shown does not constitute a limitation on the electronic device 1, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0095] For example, although not shown, the electronic device 1 can also include a power supply (such as a battery) to power each component. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management system, so that the power management system can implement functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more DC or AC power sources, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device 1 can also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not described here.

[0096] Further, the electronic device 1 can also include a network interface, which can optionally include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is typically used to establish a communication connection between the electronic device 1 and other electronic devices.

[0097] Optionally, the electronic device 1 can also include a user interface, which can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch, etc. The display can also be appropriately referred to as a display screen or a display unit, and is used to display information processed in the electronic device 1 and to display a visualized user interface.

[0098] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by this structure.

[0099] The continuous casting machine crystallizer breakout identification program 12 stored in the memory 11 in the electronic device 1 is a combination of a plurality of instructions, which, when running in the processor 10, can realize: obtaining crystallizer thermocouple data, and determining a sticking feature change moment according to the crystallizer thermocouple data; obtaining continuous casting machine pulling speed data and continuous casting machine crystallizer liquid level data in a set time interval before the sticking feature change moment; determining the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval according to the obtained continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data; determining the state of the crystallizer of the continuous casting machine according to the standard deviation; wherein when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state; and when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state.

[0100] Specifically, the specific implementation method of the processor 10 to the above instructions can refer to Figure 1 The description of related steps in the corresponding embodiments will not be repeated here. Further, the modules / units integrated by the electronic device 1 can be stored in a computer readable storage medium if they are realized in the form of software function units and sold or used as independent products. The computer readable medium can include any entity or system that can carry the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory).

[0101] The embodiment of the present application also provides a computer readable storage medium, which can be nonvolatile or volatile, and stores a computer program, which is executed by a processor to realize the following: obtaining the crystallizer thermocouple data, determining the adhesion characteristic change moment according to the crystallizer thermocouple data, obtaining the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in a set time interval before the adhesion characteristic change moment, determining the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval according to the obtained continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data, determining the state of the crystallizer of the continuous casting machine according to the standard deviation, wherein when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold value, it is determined that the crystallizer of the continuous casting machine is in a first state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold value and less than a second threshold value, it is determined that the crystallizer of the continuous casting machine is in a second state; and when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold value, it is determined that the crystallizer of the continuous casting machine is in a third state.

[0102] Specifically, the computer program is executed by the processor to realize the method, and the implementation of the method can refer to the description of the related steps in the embodiment of the continuous casting machine crystallizer breakout identification method, which is not described here.

[0103] In the several embodiments of the present application, it should be understood that the disclosed device, system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, another division manner can be used.

[0104] The modules described as separate components can or can not be physically separate, and the components displayed as modules can or can not be physical units, i.e., can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment.

[0105] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of hardware plus software functional module.

[0106] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

[0107] Therefore, embodiments should be considered in all respects as illustrative and not restrictive, the scope of the application being defined by the appended claims rather than the description given above, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. No reference signs in the claims shall be construed as limiting the scope of the claims.

[0108] Further, it is clear that the word "comprising" is not used exclusively in the sense of "consisting only of", that the singular also includes the plural and vice versa unless explicitly stated otherwise. The use of reference signs in the claims with or without the propen-dicular line shall not be construed as limiting the scope of the claims with respect to identical or similar reference signs unless explicitly stated otherwise.

[0109] However, those skilled in the art should understand that, for the above-mentioned continuous casting machine crystallizer breakout recognition method and continuous casting machine crystallizer breakout recognition system of the present application, various improvements can be made on the basis of not departing from the content of the present application. Therefore, the protection scope of the present application should be determined by the content of the appended claims.

Claims

1. A continuous casting mold breakout recognition method applied to an electronic device, characterized by, The method comprises the following steps: acquiring the crystallizer thermocouple data, and determining the adhesion characteristic change time when abnormal fluctuations or preset alarm thresholds of temperature data are detected; determining the adhesion characteristic change time according to the crystallizer thermocouple data; acquiring the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in a set time interval before the adhesion characteristic change time; determining the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data in the set time interval according to the acquired continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data; determining the state of the crystallizer of the continuous casting machine according to the standard deviation; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is less than a first threshold, it is determined that the crystallizer of the continuous casting machine is in a first state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the first threshold and less than a second threshold, it is determined that the crystallizer of the continuous casting machine is in a second state; when the standard deviation of the continuous casting machine pulling speed data and the continuous casting machine crystallizer liquid level data is greater than the second threshold, it is determined that the crystallizer of the continuous casting machine is in a third state; wherein the first state is a stable operation state of the continuous casting machine, the second state is a sub-stable operation state of the continuous casting machine, and the third state is an abnormal operation state of the continuous casting machine; carrying out continuous casting machine crystallizer breakout identification according to the state of the crystallizer of the continuous casting machine.

2. The continuous casting machine crystallizer breakout identification method according to claim 1, wherein when it is determined that the crystallizer of the continuous casting machine is in the first state, the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the continuous casting machine pulling speed data are acquired; the minimum temperature rising temperature of the upper thermocouple is acquired according to the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the minimum temperature rising temperature of the lower thermocouple is acquired according to the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the moving speed of the high temperature point time between the two thermocouples is acquired according to the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple, and then the ratio of the moving speed of the high temperature point time between the two thermocouples to the pulling speed is determined according to the moving speed of the high temperature point time between the two thermocouples and the continuous casting machine pulling speed data; the crystallizer state monitoring is carried out according to the first rule, and if the minimum temperature rising temperature of the upper thermocouple or the minimum temperature rising temperature of the lower thermocouple and the ratio of the moving speed of the high temperature point time between the two thermocouples to the pulling speed meet the first rule, a breakout alarm signal is sent. when it is determined that the crystallizer of the continuous casting machine is in the second state, the initial temperature and the maximum temperature of the upper thermocouple when the temperature rising curve appears, the initial temperature and the maximum temperature of the lower thermocouple when the temperature rising curve appears, the high temperature point time of the upper thermocouple, the high temperature point time of the lower thermocouple, the actual physical distance between the upper thermocouple and the lower thermocouple, and the continuous casting machine pulling speed data are acquired; 3. The continuous casting machine mold breakout detection method according to claim 1, characterized by, ​ The minimum temperature rise of the upper thermocouple is obtained according to the initial temperature and the maximum temperature of the upper thermocouple when the temperature rise curve appears, and the minimum temperature rise of the lower thermocouple is obtained according to the initial temperature and the maximum temperature of the lower thermocouple when the temperature rise curve appears; the speed of the high-temperature point between the two thermocouples at the high-temperature point time is obtained according to the high-temperature point time of the upper thermocouple, the high-temperature point time of the lower thermocouple, and the actual physical distance between the upper thermocouple and the lower thermocouple; and then the ratio of the speed of the high-temperature point between the two thermocouples at the high-temperature point time to the casting speed is determined according to the speed of the high-temperature point between the two thermocouples at the high-temperature point time and the casting speed data. The mold state is monitored according to the second rule; if the minimum temperature rise of the upper thermocouple or the minimum temperature rise of the lower thermocouple and the ratio of the speed of the high-temperature point between the two thermocouples at the high-temperature point time to the casting speed meet the second rule, a breakout alarm signal is sent.

4. The continuous caster mold breakout detection method according to claim 1, characterized by, When it is determined that the mold of the continuous casting machine is in the third state, the casting speed data, the mold level data of the continuous casting machine, and the mold vibration data are obtained; The abnormal state type of the continuous casting machine is determined according to the obtained casting speed data, the mold level data of the continuous casting machine, and the mold vibration data.

5. The continuous caster mold breakout detection method according to claim 4, characterized by, The abnormal state type of the continuous casting machine includes any one of a water nozzle replacement state, a tundish replacement state, an abnormal accident state, a start-up speed increase state, a stop pouring state, a speed increase state, and a speed decrease state.

6. The continuous caster mold breakout detection method according to claim 4, characterized by, After determining the abnormal state type of the continuous casting machine according to the obtained casting speed data, the mold level data of the continuous casting machine, and the mold vibration data, the method further includes, According to the abnormal state type of the continuous casting machine, the breakout monitoring is performed according to the determination rule corresponding to the abnormal state type of the continuous casting machine.

7. A continuous casting machine mold breakout identification system for identifying breakout by using the continuous casting machine mold breakout identification method according to any one of claims 1-6; the system comprises: A data acquisition unit is configured to obtain mold thermocouple data, and determine a sticking feature change time when detecting that the temperature data abnormally fluctuates or reaches a preset alarm threshold; and determine the sticking feature change time according to the mold thermocouple data; obtain the casting speed data and the mold level data of the continuous casting machine within a set time interval before the sticking feature change time; A data processing unit is configured to determine the standard deviation of the casting speed data and the mold level data of the continuous casting machine within the set time interval according to the obtained casting speed data and the mold level data of the continuous casting machine. The state determining unit is configured to determine the state of the mold of the continuous casting machine according to the standard deviation; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine mold level data is less than a first threshold value, it is determined that the mold of the continuous casting machine is in a first state; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine mold level data is greater than the first threshold value and less than a second threshold value, it is determined that the mold of the continuous casting machine is in a second state; when the standard deviation of the continuous casting machine casting speed data and the continuous casting machine mold level data is greater than the second threshold value, it is determined that the mold of the continuous casting machine is in a third state; wherein the first state is a stable operation state of the continuous casting machine; the second state is a sub-stable operation state of the continuous casting machine; and the third state is an abnormal operation state of the continuous casting machine; and the state of the mold of the continuous casting machine is used for identifying the breakout of the mold of the continuous casting machine. 8.An electronic device, comprising: The electronic device comprises a memory, a processor, and a continuous casting mold breakout identification program stored in the memory and executable on the processor, and the continuous casting mold breakout identification program, when executed by the processor, implements the steps of the continuous casting mold breakout identification method according to any one of claims 1 to 6.

9. A computer readable storage medium storing a computer program, characterized in that, The computer program, when executed by the processor, implements the continuous casting mold breakout identification method according to any one of claims 1 to 6.

Images