A copper rod continuous casting process temperature monitoring and communication control system, method and device

Abstract

The present application relates to copper rod continuous casting technical field, especially in a kind of copper rod continuous casting process temperature supervision and communication control system, method and device, system includes: information acquisition module is used to obtain several real-time temperature data;Information communication module includes signal acquisition unit, for generating analysis signal;Signal processing unit, for the priority feature of analysis signal insertion, sequencing reorganization is formed signal data set;Signal determination unit, for each analysis signal is carried out key frame information capture, and basis determination analysis signal is whether as target signal output to information processing module;Information processing module is used to accept target signal, and output casting wheel target signal corresponding state analysis report;Information control module is used to form instruction information interaction according to state analysis report, with external device through information communication module.The priority of different analysis signals is processed, the timely and accurate feedback of analysis signal is ensured, and the timeliness and effectiveness of instruction interaction are improved.

Description

Technical Field

[0001] This invention relates to the field of copper rod continuous casting technology, and in particular to a temperature monitoring and communication control system, method and apparatus for copper rod continuous casting process. Background Technology

[0002] The continuous casting machine is the core equipment of the copper rod continuous casting system. It mainly consists of components such as the casting wheel and the cooling mechanism. The casting wheel provides cooling, geometry and space for the solidification of the copper liquid, and its performance directly affects the quality of the copper billet. The cooling device cools the casting wheel and the copper rod billet through methods such as circulating water cooling to ensure the normal solidification and forming of the copper billet.

[0003] In the continuous casting process of copper rods, the temperature change of the casting wheel has a significant impact on the solidification morphology of the copper billet. By monitoring the temperature of the casting wheel, the working status of the casting wheel can be analyzed, and real-time feedback can be generated. However, due to the special working conditions on the production site, the real-time temperature data of the casting wheel is difficult to collect and the data is complex. After the processor obtains the data, it needs to process a large amount of data simultaneously, making it difficult to conduct timely and targeted analysis for different situations during the analysis process. This leads to a lag in feedback control and affects the timeliness and accuracy of decision-making.

[0004] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the present invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a temperature monitoring and communication control system, method and device for the continuous casting process of copper rods, so as to realize priority processing of different analysis signals, ensure timely and accurate feedback of analysis signals, and improve the timeliness and effectiveness of command interaction.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a temperature monitoring and communication control system for continuous casting of copper rods, comprising: an information communication module and an information acquisition module, an information processing module and an information control module connected thereto;

[0007] The information acquisition module is used to acquire several real-time temperature data of the casting wheel during the continuous casting process of copper rods;

[0008] The information communication module includes:

[0009] A signal acquisition unit is used to generate analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals.

[0010] The signal processing unit is used to perform priority processing on the analyzed signals, insert priority features into each analyzed signal, and sort and reorganize them to form a signal dataset.

[0011] The signal determination unit is used to capture keyframe information for each analysis signal in the signal dataset and determine whether the analysis signal should be output as a target signal to the information processing module based on the priority feature.

[0012] The information processing module is used to receive the target signal, perform corresponding analysis and processing steps based on the target signal, and output a status analysis report corresponding to the target signal of the casting wheel.

[0013] The information control module is used to generate improvement instructions based on the status analysis report, and to interact with external devices through the information communication module to exchange instruction information.

[0014] Furthermore, the information acquisition module includes:

[0015] The data acquisition unit is used to acquire multi-dimensional image information and the first analysis signal of the casting wheel;

[0016] The data processing unit is used to construct a mimicry model with structural and dimensional features corresponding to the casting wheel based on the first analysis signal, and simultaneously output the second analysis signal.

[0017] The scheme construction unit is used to analyze and process the mimicry model based on the second analysis signal, and determine and output the temperature measurement scheme of the casting wheel;

[0018] The scheme execution unit is used to determine the boundary conditions of the mimicry model according to the temperature measurement scheme, and to perform temperature simulation on the mimicry model according to the boundary conditions to obtain predicted temperature data;

[0019] The scheme output unit is used to exchange scheme information with external devices through the information communication module, and to conduct temperature measurement tests on the casting wheel according to the temperature measurement scheme to obtain the real-time temperature data.

[0020] Furthermore, the formation process of the overall analysis signal includes the following steps:

[0021] Determine the real-time temperature data of each monitoring point on the casting wheel, and preprocess the real-time temperature data;

[0022] Based on the real-time temperature data, a moving average algorithm is used to determine the temperature information value of each monitoring point. The temperature information value includes the average temperature within a set time interval and the standard deviation and range between each monitoring point.

[0023] The temperature information values ​​of each monitoring point are collected, summarized, and assigned to the overall analysis signal.

[0024] Furthermore, the formation process of the local analysis signal includes the following steps:

[0025] The surface and inner space of the casting wheel are divided into local areas, and each local area includes at least one monitoring point. Real-time temperature data in each local area are determined in turn.

[0026] Using the real-time temperature data, temperature characteristic values ​​are determined sequentially for each local region, including the highest temperature, the lowest temperature, and the temperature gradient.

[0027] The temperature characteristic values ​​of each local area are collected and summarized and assigned as local analysis signals.

[0028] Furthermore, the formation process of the change analysis signal includes the following steps:

[0029] Collect real-time temperature data from various monitoring points on the casting wheel at continuous time points to form a temperature time series;

[0030] The temperature change rate under the temperature time series of each monitoring point is calculated using the finite difference method to obtain the temperature change rate series of each point.

[0031] The temperature change rate sequence of each monitoring point is compiled and summarized and assigned as a change analysis signal.

[0032] Furthermore, the formation process of the anomaly analysis signal includes the following steps:

[0033] Real-time temperature data of each monitoring point of the casting wheel is acquired. A score conversion algorithm based on machine learning is used to calculate the effective score corresponding to each real-time temperature data and determine whether it exceeds the confidence interval of the normal range. The confidence interval is obtained by the information acquisition module through dynamic analysis of the predicted temperature data output by the scheme execution unit.

[0034] When the data exceeds the confidence interval, the monitoring point corresponding to the real-time temperature data is determined to be an anomaly. The temperature data features of the anomaly point and its adjacent distributed monitoring points are extracted, and the anomaly feature information is obtained by extracting and analyzing the temperature data features.

[0035] The abnormal feature information is collected and summarized and assigned as an abnormal analysis signal.

[0036] Furthermore, the step of prioritizing the analyzed signals, inserting priority features into each analyzed signal, and sorting and reorganizing them to form a signal dataset includes the following steps:

[0037] Within the same unit time interval, at least four priority features are set, and their levels are arranged sequentially from the zeroth priority.

[0038] The initial priority features of the overall analysis signal, the local analysis signal, and the change analysis signal are assigned to the third priority, and the initial priority feature of the anomaly analysis signal is assigned to the first priority.

[0039] Construct correlation feature rules between different analysis signals, and when the correlation feature rules are triggered, perform correlation marking between the related analysis signals;

[0040] Based on the differences between the information data contained in each analysis signal and the confidence intervals of the fluctuation range and the duration range, and combined with the results of the correlation feature determination, the priority features of the current analysis signal and the associated analysis signals are determined to be either increased, maintained, or decreased.

[0041] Based on the priority characteristics of the analyzed signals, priority characteristics are reassigned to the analyzed signals sequentially from the zeroth priority, and the recombined signals form a signal dataset.

[0042] Furthermore, the step of extracting keyframe information from each analyzed signal in the signal dataset and determining whether the analyzed signal should be output as a target signal to the information processing module based on the priority feature includes the following steps:

[0043] The analysis signal corresponding to the zeroth priority in the information dataset is selected, and the analysis signals corresponding to the other priority features are retained as reference signals.

[0044] Capture key frame information of the current analysis signal and construct a key frame feature vector containing timestamps. The key frame information includes any one of temperature information values, temperature feature values, temperature change rate sequences, or abnormal feature information.

[0045] Based on the data format and communication protocol, the current analysis signal and its corresponding key frame feature vector are output as target signals to the information processing module, while the analysis signal corresponding to the next priority feature is extracted as a candidate signal.

[0046] Repeat the above steps until every analyzed signal and its corresponding keyframe feature vector in the signal dataset are sent to the information processing module.

[0047] The present invention also provides a method for temperature monitoring and control in the continuous casting process of copper rods, using the temperature monitoring and communication control system for the continuous casting process of copper rods as described in any of the preceding claims, comprising the following steps:

[0048] The information acquisition module acquires several real-time temperature data of the casting wheel during the continuous casting process of copper rod;

[0049] The signal acquisition unit generates analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals.

[0050] The signal processing unit performs priority processing on the analyzed signals, inserts priority features into each analyzed signal, and sorts and reassembles them to form a signal dataset.

[0051] The signal determination unit captures keyframe information for each analyzed signal in the signal dataset and determines whether the analyzed signal should be output as a target signal to the information processing module based on the priority feature.

[0052] The information processing module receives the target signal, performs corresponding analysis and processing steps based on the target signal, and outputs a status analysis report corresponding to the target signal of the casting wheel.

[0053] The information control module generates improvement instructions based on the status analysis report and interacts with external devices through the information communication module to form improvement instruction exchanges.

[0054] The present invention also provides a temperature monitoring and control device for the continuous casting process of copper rods, using the temperature monitoring and communication control system for the continuous casting process of copper rods as described in any of the preceding claims, comprising:

[0055] The housing includes a plurality of temperature sensors, a temperature recorder, and an energy storage device built into the housing. The sensing ends of the temperature sensors are led out from the openings in the housing and are respectively sealed and assembled at set points on the casting wheel. The temperature recorder is communicatively connected to each of the temperature sensors to read and record each real-time temperature data. The energy storage device is used to supply energy to the temperature sensors and the temperature recorder.

[0056] The beneficial effects of this invention are as follows: This invention provides real-time temperature data through an information acquisition module, and the information communication module generates various types of analysis signals and performs operations such as priority processing, key frame information capture, and target signal determination. This enables the information processing module to quickly and accurately generate targeted status analysis reports based on the current real-time temperature data and the priority of different analysis signals. Consequently, the information control module can promptly generate accurate feedback based on the status analysis reports. The overall control system helps to realize priority processing of different analysis signals, ensure timely and accurate feedback of analysis signals, improve the timeliness and effectiveness of command interaction, enable the system to operate efficiently and orderly, and ensure the stability of the copper rod continuous casting process and the quality of the copper billet. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of the temperature monitoring and communication control system for the continuous casting process of copper rods in an embodiment of the present invention;

[0059] Figure 2 This is a schematic diagram illustrating the formation process of the overall analysis signal in an embodiment of the present invention;

[0060] Figure 3 This is a schematic diagram illustrating the formation process of the local analysis signal in an embodiment of the present invention;

[0061] Figure 4 This is a schematic diagram illustrating the formation process of the change analysis signal in an embodiment of the present invention;

[0062] Figure 5 This is a schematic diagram illustrating the formation process of the anomaly analysis signal in an embodiment of the present invention;

[0063] Figure 6 This is a flowchart illustrating the priority processing in an embodiment of the present invention;

[0064] Figure 7 This is a schematic diagram of the target signal output determination process in an embodiment of the present invention;

[0065] Figure 8 This is a schematic diagram showing the distribution of the temperature measurement scheme in an embodiment of the present invention;

[0066] Figure 9 This is a schematic diagram illustrating the analysis process of the change analysis signal when the casting wheel rotates once in an embodiment of the present invention;

[0067] Figure 10 This is a schematic diagram of the analysis results of the abnormal analysis signal in an embodiment of the present invention;

[0068] Figure 11 This is a flowchart illustrating the temperature monitoring and communication control method for the continuous casting process of standard copper rods in an embodiment of the present invention. Detailed Implementation

[0069] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0070] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0072] like Figures 1 to 10 The temperature monitoring and communication control system for the continuous casting process of copper rod shown includes: an information communication module and an information acquisition module, an information processing module and an information control module connected to it.

[0073] The information acquisition module is used to acquire several real-time temperature data of the casting wheel during the continuous casting process of copper rods;

[0074] The information and communication module includes:

[0075] The signal acquisition unit is used to generate analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals.

[0076] The signal processing unit is used to prioritize the analyzed signals, insert priority features into each analyzed signal, and sort and reorganize them to form a signal dataset.

[0077] The signal determination unit is used to capture key frame information for each analyzed signal in the signal dataset and determine whether the analyzed signal should be output to the information processing module as a target signal based on priority features.

[0078] The information processing module is used to receive the target signal, perform corresponding analysis and processing steps based on the target signal, and output a status analysis report corresponding to the target signal of the casting wheel;

[0079] The information control module is used to generate improvement instructions based on the status analysis report and to exchange instruction information with external devices through the information communication module.

[0080] This invention provides real-time temperature data through an information acquisition module, and an information communication module generates various types of analytical signals and performs priority processing, key frame information capture, and target signal determination. This enables the information processing module to quickly and accurately generate targeted status analysis reports based on the current real-time temperature data and the priority of different analytical signals. Consequently, the information control module can promptly generate accurate feedback based on the status analysis reports. The overall control system helps to achieve priority processing of different analytical signals, ensures timely and accurate feedback of analytical signals, improves the timeliness and effectiveness of command interaction, and enables the system to operate efficiently and orderly, ensuring the stability of the copper rod continuous casting process and the quality of the copper billet.

[0081] The information acquisition module is used to acquire several real-time temperature data of the casting wheel in the continuous casting of copper rods. By providing timely and accurate temperature data, the effectiveness and accuracy of subsequent decisions can be ensured, thereby realizing effective monitoring and feedback of the temperature status of the casting wheel. In the acquisition process, temperature sensors distributed at several points on the casting wheel are typically used for monitoring, forming real-time temperature data including the temperature of the first point, the temperature of the second point, ..., the temperature of the Nth point. The real-time temperature data should also include the temperature of the internal space of the crystallizer in the continuous casting machine, that is, the relevant temperature of the working environment of the casting wheel, to ensure the accuracy and comprehensiveness of the data selection results.

[0082] The information communication module is used to realize the transmission of signals and information between the information acquisition module, information processing module, and information control module, and to form information and command interaction with external devices. It is the core connection hub of the system, which can ensure the smooth transmission of information and commands between various modules and ensure the collaborative work of the entire system.

[0083] Specifically, the signal acquisition unit can generate various analysis signals, including overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals, enabling comprehensive and multi-dimensional analysis of the casting wheel's temperature state and helping to confirm temperature changes from different perspectives. The signal processing unit can prioritize different analysis signals, insert priority features, and sort and reorganize them to form a signal dataset. This allows for effective differentiation of the importance and urgency of different analysis signals, prioritizing the processing and analysis of highly important and urgent signals. This avoids wasting processing resources and time due to simultaneous analysis of multiple signals, thereby improving processing efficiency and control response interaction rate. The signal determination unit plays a screening and filtering role, ensuring that only signals with key information and high priority can enter the subsequent in-depth analysis stage, further improving the targeting and effectiveness of information processing and reducing data interference and processing burden.

[0084] The information processing module is used to analyze and process the current input analysis signal and related real-time temperature data, so as to accurately determine the current temperature status and abnormal conditions of the casting wheel and present the corresponding status analysis report. In this process, since the information communication module has already performed preliminary processing and priority sorting based on the initially acquired real-time temperature data, the information processing module only needs to perform corresponding analysis and processing steps on the targeted analysis signal, which greatly improves the data processing efficiency.

[0085] The information control module can generate corresponding improvement instructions based on the current analysis results, enabling staff to adjust and optimize relevant parameters and operations in the continuous casting process in a timely manner, such as cooling intensity and casting wheel speed, to ensure the service life of the casting wheel and the normal solidification and forming of the copper billet.

[0086] Based on the above embodiments, the information acquisition module includes:

[0087] The data acquisition unit is used to acquire multi-dimensional image information and the first analysis signal of the casting wheel. Specifically, the multi-dimensional image information can realistically reflect the appearance, structure and other features of the casting wheel from different perspectives and dimensions, providing a data foundation for the subsequent construction of the mimicry model. The multi-dimensional image information can be acquired through image acquisition devices such as cameras, while the first analysis signal provides signal instructions for the construction of the mimicry model to ensure the accuracy of the conversion results between the multi-dimensional image information and the mimicry model during the construction process.

[0088] The data processing unit is used to construct a mimicry model of the casting wheel with structural and dimensional features based on the multi-dimensional image information, using the first analysis signal, and simultaneously outputting a second analysis signal. After acquiring the multi-dimensional image information of the casting wheel, the unit analyzes, processes, and fuses the basic parameters and feature information of the multi-dimensional image information based on the first analysis signal, extracting structural features such as shape and holes, as well as dimensional features such as length and diameter on the casting wheel. Based on the information obtained from the analysis, a mimicry model of the casting wheel is constructed, which can intuitively and accurately reflect the actual situation of the casting wheel. While generating the mimicry model, the unit also outputs a second analysis signal, which provides signal instructions for constructing the temperature measurement scheme of the casting wheel to ensure that the output temperature measurement scheme meets the actual temperature measurement requirements of the casting wheel.

[0089] The scheme construction unit is used to analyze and process the mimicry model based on the second analysis signal, determine and output the temperature measurement scheme of the casting wheel; after obtaining the mimicry model corresponding to the casting wheel, based on the second signal, through relevant temperature measurement strategy algorithms or empirical models, determine the key parts to be considered on the casting wheel, the distribution of temperature measurement points, temperature measurement conditions and other requirements, thereby specifying and forming a complete temperature measurement scheme;

[0090] The scheme execution unit is used to determine the boundary conditions of the mimicry model according to the temperature measurement scheme, and to perform temperature simulation on the mimicry model based on the boundary conditions to obtain predicted temperature data. After obtaining the temperature measurement scheme, according to the requirements of the scheme for the arrangement of temperature measurement points, it can determine the corresponding boundary conditions on the mimicry model, such as the initial temperature of the casting wheel in contact with the cooling water, and the heat dissipation simulation under the rotation speed of the casting wheel. Then, it uses thermodynamic related algorithms to perform temperature simulation on the mimicry model, predict the temperature distribution of the casting wheel during the continuous casting process, and obtain predicted temperature data. This helps to understand the temperature change trend of the casting wheel in advance, and also provides a reference and expected comparison for actual temperature measurement, so that timely auxiliary feedback can be generated during the temperature measurement process.

[0091] The scheme output unit is used to exchange scheme information with external devices through the information communication module, and to conduct temperature measurement tests on the casting wheel according to the scheme to obtain real-time temperature data. By exchanging scheme information with external devices through the information communication module, external devices such as temperature measuring instruments and production control systems can obtain the scheme and perform corresponding temperature measurement preparation work or adjust production parameters according to the scheme requirements. On this basis, actual temperature measurement tests are conducted on the casting wheel during the copper rod continuous casting process according to the scheme to obtain real-time temperature data of the casting wheel, thereby truly and comprehensively reflecting the temperature distribution of the casting wheel, so as to facilitate further analysis and processing by the subsequent information processing module.

[0092] Among them, such as Figure 8As shown, for an existing SCR casting wheel with an outer surface height of 120.65mm, a specific temperature measurement scheme can be provided. Specifically, the temperature of the casting wheel is measured using a thermocouple method. A K-type probe-type armored thermocouple (model JSS-109, probe diameter 3mm, temperature range 0~1200℃, made of Inconel 1600 material) is selected and used in conjunction with an ST1008A / 8-channel input thermocouple temperature recorder with a measurement range of -200~1300℃ for multi-channel temperature data acquisition. The data acquisition interval is 1 second, the storage interval is 3 seconds, and the test cycle is 10 days. Considering the differences in water cooling distribution, structure, and thickness between the inner and outer sides of the casting wheel, as well as the influence of gravity on the casting process, two temperature measurement points are arranged on the inner and outer sides of the casting wheel respectively. The scheme considers the dimensions and structure of the casting wheel and... To mitigate the impact on service life, the two holes on the outer side of the casting wheel are positioned 30mm and 60mm from the edge of the steel strip, respectively. The two thermocouple pre-embedded holes on the inner side of the casting wheel are pre-set at the center of the inner side and 68mm from the side, respectively, with a diameter of 5mm. Considering safety and testing stability during use, the depth of the two outer holes is set to 30mm, and the depth of the two inner holes is set to 20mm. Considering the influence of thermocouple wiring, equipment installation, and drilling on the strength of the casting wheel, the included angle between the cross-sections of the two outer holes is 1°, the included angle between the cross-sections of adjacent inner and outer holes is 4°, and the included angle between the cross-sections of the two inner holes is 3°. Considering the cooling spray water pressure and flow rate, pins are used for fixing, and high-temperature sealant is used for sealing.

[0093] Based on the above embodiments, the overall signal formation process is analyzed, including the following steps:

[0094] The real-time temperature data of each monitoring point on the casting wheel is determined and the real-time temperature data is preprocessed. The preprocessing operation can remove noise and interference from the data. It can usually be done by filtering, data correction, missing data filling and other operations to improve the accuracy and completeness of the data, thereby ensuring the accuracy of the subsequent analysis signal formation and analysis process.

[0095] Based on real-time temperature data, a moving average algorithm is used to determine the temperature information values ​​at each monitoring point. The temperature information values ​​include the average temperature over a set time interval, as well as the standard deviation and range between each monitoring point. The moving average algorithm can smooth out fluctuations in temperature data and reduce the impact of short-term random fluctuations on temperature analysis. The average temperature value reflects the overall temperature level of the monitoring point during the time interval, while the standard deviation and range reflect the degree of dispersion and range of temperature variation between different monitoring points, which helps to determine the non-uniformity of temperature distribution at different locations on the casting wheel.

[0096] The temperature information values ​​of each monitoring point are collected and summarized and assigned to the overall analysis signal. The overall analysis signal contains the temperature information values ​​of each monitoring point, and also provides signal instructions for the information processing module to execute the analysis and processing steps corresponding to the overall analysis signal, so that the information processing module can perform a comprehensive analysis of the temperature distribution and changes of the casting wheel.

[0097] Based on the above embodiments, the formation process of the local analysis signal includes the following steps:

[0098] The surface and inner space of the casting wheel are divided into local areas, and each local area includes at least one monitoring point. Real-time temperature data in each local area are determined in turn. The local area division can be based on factors such as the geometry of the casting wheel and the spray cooling conditions. The surface and inner space of the casting wheel can be reasonably divided, but it is necessary to ensure that there is at least one temperature monitoring point in each local area to obtain the real-time temperature data in that area.

[0099] By using real-time temperature data, the temperature characteristic values ​​of each local area are determined sequentially. The temperature characteristic values ​​include the highest temperature, the lowest temperature, and the temperature gradient. The temperature characteristic values ​​can reflect the temperature information of that local area on the casting wheel. The highest and lowest temperatures can be determined based on the temperature distribution. The temperature gradient can be determined by the temperature difference between the highest and lowest temperatures and the corresponding spatial distribution, which helps to determine the specific temperature distribution in that local area.

[0100] The temperature characteristic values ​​of each local area are collected and summarized and assigned as local analysis signals. The local analysis signals contain the temperature characteristic values ​​of the local area and also provide signal instructions for the information processing module to execute the analysis and processing steps corresponding to the local analysis signals, so that the information processing module can perform targeted analysis of the temperature distribution and changes in the local area of ​​the casting wheel.

[0101] Based on the above embodiments, the formation process of the change analysis signal includes the following steps:

[0102] Real-time temperature data from various monitoring points on the casting wheel are collected at continuous time points to form a temperature time series. The temperature time series can reflect the trend of temperature change over time at each monitoring point. It is formed by arranging the real-time temperature data collected at each monitoring point at a series of continuous time intervals in chronological order. For example, the temperature time series of monitoring point A can be represented as [T1_A,T2_A,T3_A,…,Tn_A], where T1_A represents the temperature value at the first time point and Tn_A represents the temperature value at the nth time point.

[0103] The temperature change rate under the temperature time series of each monitoring point is calculated using the finite difference method to obtain the temperature change rate sequence of each point. The finite difference method is to approximate the temperature change rate by the difference between the temperature data of adjacent time points, thereby obtaining the temperature change rate sequence, which can reflect the speed of temperature change over time at each monitoring point. For example, the temperature change rate of monitoring point A can be expressed as: ΔTi=(T(i+1)-Ti) / Δt, where ΔTi represents the temperature change rate in the i-th time interval, T(i+1) and Ti represent the temperature values ​​at the i+1 and i-th time points, respectively, and Δt is the time interval. The temperature change rate sequence of each monitoring point is calculated in sequence. For example, the temperature change rate sequence of monitoring point A can be expressed as [ΔT1_A,ΔT2_A,ΔT3_A,…,ΔT(n-1)_A].

[0104] The temperature change rate sequence of each monitoring point is compiled and summarized and assigned as a change analysis signal. The change analysis signal contains the temperature change rate sequence of each monitoring point, and also provides signal instructions for the information processing module to execute the analysis and processing steps corresponding to the change analysis signal, so that the information processing module can perform targeted temperature change analysis on the area where each monitoring point on the casting wheel is located.

[0105] Based on the above embodiments, the process of forming anomaly analysis signals includes the following steps:

[0106] Real-time temperature data from each monitoring point on the casting wheel is acquired. A machine learning-based fractional conversion algorithm is used to calculate the effective score for each real-time temperature data point and determine whether it exceeds the confidence interval of the normal range. The confidence interval is dynamically obtained by the information acquisition module based on the predicted temperature data output by the scheme execution unit. The predicted temperature data is obtained by simulating the temperature measurement scheme on the mimicry model. The machine learning-based fractional conversion algorithm is trained based on historical temperature data and corresponding production status. Through the form of fractional conversion and the matching judgment of confidence interval, it is possible to comprehensively determine whether an abnormal situation has occurred at the monitoring point.

[0107] When the data exceeds the confidence interval, the monitoring point corresponding to the real-time temperature data is determined to be an anomaly. The temperature data features of the anomaly point and its adjacent monitoring points are extracted, and the anomaly feature information is obtained by extracting and analyzing the temperature data features. In order to reduce the false positive rate, multiple repeated verifications can be set, and the temperature data features of the adjacent monitoring points that may be affected are extracted, such as the temperature change trend, the duration of the temperature anomaly, and the degree of deviation between the abnormal temperature and the normal temperature. The above features are extracted and summarized to form the anomaly feature information.

[0108] The abnormal feature information is collected and summarized and assigned as an abnormal analysis signal. The abnormal analysis signal contains abnormal feature information of a specific monitoring point, and also provides signal instructions for the information processing module to execute the analysis and processing steps corresponding to the abnormal analysis signal, so that the information processing module can perform targeted abnormal situation analysis on the monitoring point where the temperature anomaly occurs on the casting wheel and the area that may be affected.

[0109] Based on the above embodiments, priority processing is performed on the analyzed signals, priority features are inserted into each analyzed signal, and the signals are sorted and reorganized to form a signal dataset, including the following steps:

[0110] Within the same unit time interval, at least four priority features are set, with the levels arranged sequentially from the zeroth priority. The zeroth priority is the highest priority, indicating that the signal needs to be processed first, and the subsequent priorities are reduced in order to ensure that signals of different importance can be processed in an orderly manner.

[0111] The initial priority characteristics of the overall analysis signal, local analysis signal, and change analysis signal are assigned to the third priority, while the initial priority characteristic of the anomaly analysis signal is assigned to the first priority. During the initial setting process, the priority level of the overall analysis signal, local analysis signal, and change analysis signal is in a medium state, with relatively low importance, and can be postponed for later processing. However, the initial priority of the anomaly analysis signal is set to the first priority, and under no other special circumstances, it needs to be analyzed and processed first to eliminate anomalies in a timely manner.

[0112] Construct correlation feature rules between different analytical signals. When the correlation feature rules are triggered, the related analytical signals are marked. After real-time temperature data is acquired at the same monitoring point, there may be mutual influence between different analytical signals. For example, when an abnormal analytical signal is generated, the change analytical signal in its area also has a correlation. Therefore, when judging the priority of different analytical signals, it is necessary to comprehensively judge the mutual influence between different analytical signals in order to improve the accuracy of the comprehensive judgment result.

[0113] Based on the differences between the information data contained in each analysis signal and the confidence intervals of the fluctuation range and duration range, and combined with the results of the correlation feature determination, the priority feature of the current analysis signal and its associated analysis signals is determined to be either increased, maintained, or decreased. For example, if the temperature change rate of the current analysis signal exceeds the confidence interval for a long time, and there are also abnormal analysis signals associated with it, then the priority feature of the current analysis signal needs to be increased to the next higher interval. If there are time points in the interval that exceed the confidence interval, then the current priority is maintained for subsequent analysis. If it remains within a stable confidence interval, then the current analysis signal can be decreased to allow processing time and resources for other analysis signals in an emergency.

[0114] Based on the priority characteristics of the analyzed signals, priority characteristics are reassigned to the analyzed signals sequentially from the zeroth priority, and the recombined signals form a signal dataset. This allows the system to efficiently analyze and respond to the signals in order by simply reading the priority numbers in subsequent processing, ensuring that critical analyzed signals are processed in a timely manner, improving the overall system efficiency and response speed to abnormal situations.

[0115] The priority level of the current analysis signal can be determined by the following methods. Of course, other methods can also be used to determine the priority level of different analysis signals, and no specific limitations are made here.

[0116] Specifically, information extraction and analysis are performed sequentially on the anomaly analysis signal, overall analysis signal, local analysis signal, and change analysis signal. Then, it is sequentially determined whether the anomaly feature information, temperature information value, temperature feature value, and temperature change rate sequence conform to the fluctuation range confidence interval. When the fluctuation range confidence interval is exceeded, the corresponding analysis signal is elevated to the next higher priority feature. When the fluctuation range confidence interval is not exceeded, it is sequentially determined whether the anomaly feature information, temperature information value, temperature feature value, and temperature change rate sequence conform to the duration range confidence interval. When the duration range confidence interval is exceeded, the corresponding analysis signal maintains its current priority feature. When the duration range confidence interval is not exceeded, the corresponding analysis signal is degraded to the next lower priority feature. If the current analysis signal has associated analysis signals, the priority features of the associated analysis signals change synchronously with the current analysis signal.

[0117] Based on the above embodiments, keyframe information is captured for each analysis signal in the signal dataset, and the analysis signal is determined as a target signal to be output to the information processing module based on priority features, including the following steps:

[0118] The analysis signal corresponding to the zeroth priority in the information dataset is selected, and the analysis signals corresponding to the other priority features are retained as reference signals; that is, the analysis signal with the highest priority level is selected first for target signal determination, and the other analysis signals are processed in order of priority.

[0119] The system captures key frame information of the current signal being analyzed and constructs a key frame feature vector containing timestamps. Key frame information is data that reflects the key characteristics of the signal being analyzed at a specific moment. Depending on the type of signal being analyzed, key frame information may include any one of the following: temperature information values, temperature feature values, temperature change rate sequences, or abnormal feature information. The timestamp is used to record the specific moment corresponding to the key frame information so that the change time and sequence of the signal can be accurately recorded and determined in subsequent analysis and processing.

[0120] Based on the data format and communication protocol, the current analysis signal and its corresponding keyframe feature vector are output as target signals to the information processing module. During the transmission process, it is ensured that the target signal conforms to the data transmission format requirements and is encapsulated and transmitted in accordance with the communication protocol to ensure that the signal can be accurately transmitted between modules within the system. At the same time, the analysis signal corresponding to the next priority feature is extracted as a candidate signal to ensure the continuity and orderliness of signal processing and to ensure that the system can efficiently process each analysis signal in sequence.

[0121] Repeat the above steps, that is, select the next priority analysis signal in sequence, capture its key frame information and construct key frame feature vectors, send the analysis signal that meets the requirements as the target signal to the information processing module, and extract the analysis signal with a lower priority as the candidate signal; until every analysis signal in the signal dataset and its corresponding key frame feature vector are sent to the information processing module, and ensure that all analysis signals can be processed and analyzed in a timely manner, so as to ensure the comprehensiveness and accuracy of temperature monitoring and analysis of the casting wheel during the copper rod continuous casting process.

[0122] After receiving the target signal, the information processing module can perform corresponding analysis and processing based on the currently input analysis signal and related real-time temperature data, thereby accurately judging the current temperature status and abnormal conditions of the casting wheel and presenting it as a corresponding status analysis report.

[0123] Specifically, a detailed state analysis report is provided under the above temperature measurement scheme. When the received target signal is the overall analysis signal, the real-time temperature data and temperature information values ​​from different holes indicate that the temperature variation range of the two holes on the outer side of the casting wheel is large and unstable, with the temperature variation range between 80℃ and 210℃ and between 80℃ and 240℃. The temperature variation of the two holes on the inner side of the casting wheel is relatively stable, with the temperature difference between the two holes not being very large, and the temperature variation range between 70℃ and 105℃. After analysis, the suspected cause of the unstable temperature at the two holes on the side is: after the billet leaves the crystallizer, it will experience a certain degree of lateral movement in the horizontal direction, which leads to a change in the lateral contact state between the billet and the casting wheel. However, due to the effect of gravity, the vertical contact between the billet and the casting wheel is relatively stable, resulting in relatively small temperature fluctuations on the inner side.

[0124] When the received target signal is a local analysis signal, a local area containing an outer hole in the casting wheel during the start-up phase is extracted. Through joint analysis of the real-time temperature data and temperature characteristic values ​​of this hole and the internal space of the crystallizer, it is determined that the reason for the slow temperature rise of the casting wheel after pre-operation is that copper liquid pouring has not started. The reason for the temperature fluctuation after pouring starts is that the casting wheel is simultaneously heated by the copper liquid and cooled by the cooling water. During this process, the reason for the temperature rise in the internal space of the crystallizer is the heat released by the crystallization of copper liquid.

[0125] like Figures 9 to 10 As shown, when the received target signal is a change analysis signal, the temperature changes in each spray position area of ​​the crystallizer are determined by analyzing the real-time temperature data of different holes under different area divisions and the temperature change plastic cloth sequence. The following analysis results are given: The temperature drop rate and cooling effect of the casting wheel are related to the water flow rate and the proximity of the spray area. However, there are also abnormal areas. In some areas, the temperature drop rate is slow when the water flow rate increases. In this case, an abnormal analysis signal is formed. It is necessary to comprehensively consider the abnormal feature information and the temperature change rate. The analysis determines that the area is the fourth spray zone on the inner side of the casting wheel, which is exactly the lowest end of the vertical plane of the casting wheel. The two sides of the casting wheel are fixed by the spokes. The spokes are in close contact with the inner side of the casting wheel. The spokes of the casting wheel have a certain height, which causes the cooling water sprayed from the nozzles to not be discharged in time, thus forming water accumulation at the bottom. This changes the original spray cooling method to ordinary water cooling. At the same time, the water accumulation is heated by the casting wheel, causing the water temperature to rise, which reduces the cooling effect and cooling efficiency of the casting wheel at this point.

[0126] When the analysis results obtained by the information control module do not meet expectations, corresponding improvement instructions need to be generated based on the current analysis results. Timely intervention is required to avoid the phenomenon of the solidification line of the billet shifting due to the difference in cooling intensity between the inner side of the casting wheel and the steel strip side during subsequent work. For example, the output may be: change the structure of the casting wheel spokes to drain the accumulated water, or control the solidification structure of the billet, or add an additional spray area to improve the cooling effect of the casting wheel.

[0127] like Figure 11 As shown, the present invention also provides a method for temperature monitoring and communication control in the continuous casting process of copper rods. The method using the temperature monitoring and communication control system for the continuous casting process of copper rods as described above includes the following steps:

[0128] The information acquisition module acquires several real-time temperature data of the casting wheel during the continuous casting process of copper rods;

[0129] The signal acquisition unit generates analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals.

[0130] The signal processing unit performs priority processing on the analyzed signals, inserts priority features into each analyzed signal, and sorts and reorganizes them to form a signal dataset.

[0131] The signal determination unit captures keyframe information for each analyzed signal in the signal dataset and determines whether the analyzed signal should be output as a target signal to the information processing module based on priority features.

[0132] The information processing module receives the target signal, performs corresponding analysis and processing steps based on the target signal, and outputs a status analysis report corresponding to the target signal of the casting wheel.

[0133] The information control module generates improvement instructions based on the status analysis report and interacts with external devices through the information communication module to form improvement instruction exchanges.

[0134] This invention provides real-time temperature data through an information acquisition module, and an information communication module generates various types of analytical signals and performs priority processing, key frame information capture, and target signal determination. This enables the information processing module to quickly and accurately generate targeted status analysis reports based on the current real-time temperature data and the priority of different analytical signals. Consequently, the information control module can promptly generate accurate feedback based on the status analysis reports. The overall control system helps to achieve priority processing of different analytical signals, ensures timely and accurate feedback of analytical signals, improves the timeliness and effectiveness of command interaction, and enables the system to operate efficiently and orderly, ensuring the stability of the copper rod continuous casting process and the quality of the copper billet.

[0135] The specific working process of the above method has been explained in the above embodiments, and will not be repeated here.

[0136] The present invention also provides a temperature monitoring and control device for a copper rod continuous casting process, using the temperature monitoring and communication control system for a copper rod continuous casting process as described in any of the above claims, comprising:

[0137] The housing includes several temperature sensors, a temperature recorder, and an energy storage device built into it. The sensing ends of the temperature sensors are led out from the openings in the housing and are respectively sealed and mounted at the set points on the casting wheel. The temperature recorder is connected to each temperature sensor to read and record each sensed temperature data in real time. The energy storage device is used to supply power to the temperature sensors and the temperature recorder.

[0138] As shown in the specific structural form of the temperature sensing element provided in the above embodiments, the temperature sensing element can be selected according to the corresponding model and style of the output temperature measurement scheme. Similarly, the temperature recorder can also be selected with a suitable model and style. In this embodiment, the temperature sensing element selected is a K-type probe-type armored thermocouple, which has the characteristics of high sensitivity, good stability and wide applicability. It can provide accurate temperature readings in the extreme high temperature environment of copper rod continuous casting. At the same time, in order to prevent the high temperature environment near the casting wheel and copper liquid splashing from damaging the thermocouple tail lead wire during continuous casting, the thermocouple probe length can be customized to 1m.

[0139] In addition, to ensure the continuity and integrity of real-time temperature data, the temperature recorder must be kept in normal working condition at all times, continuously powered by energy storage devices to ensure the battery life. Furthermore, the wiring terminals of the temperature recorder, temperature sensor, and energy storage devices can all be encased in a housing structure, with signal lines led out through openings in the housing structure and sealed to prevent moisture damage to the equipment and ensure the comprehensiveness and accuracy of real-time temperature data acquisition.

[0140] Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to this invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A temperature monitoring and communication control system for continuous casting of copper rods, characterized in that, include: The information communication module, and the information acquisition module, information processing module, and information control module connected to it in communication; The information acquisition module is used to acquire several real-time temperature data of the casting wheel during the continuous casting process of copper rods; The information communication module includes: A signal acquisition unit is used to generate analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals. The signal processing unit is used to perform priority processing on the analyzed signals, insert priority features into each analyzed signal, and sort and reorganize them to form a signal dataset. The signal determination unit is used to capture keyframe information for each analysis signal in the signal dataset and determine whether the analysis signal should be output as a target signal to the information processing module based on the priority feature. The information processing module is used to receive the target signal, perform corresponding analysis and processing steps based on the target signal, and output a status analysis report corresponding to the target signal of the casting wheel. The information control module is used to generate improvement instructions based on the status analysis report, and to interact with external devices through the information communication module to exchange instruction information. The information acquisition module includes: The data acquisition unit is used to acquire multi-dimensional image information and the first analysis signal of the casting wheel; The data processing unit is used to construct a mimicry model with structural and dimensional features corresponding to the casting wheel based on the first analysis signal, and simultaneously output the second analysis signal. The scheme construction unit is used to analyze and process the mimicry model based on the second analysis signal, and determine and output the temperature measurement scheme of the casting wheel; The scheme execution unit is used to determine the boundary conditions of the mimicry model according to the temperature measurement scheme, and to perform temperature simulation on the mimicry model according to the boundary conditions to obtain predicted temperature data; The scheme output unit is used to exchange scheme information with external devices through the information communication module, and to conduct temperature measurement tests on the casting wheel according to the temperature measurement scheme to obtain the real-time temperature data.

2. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 1, characterized in that, The formation process of the overall analysis signal includes the following steps: Determine the real-time temperature data of each monitoring point on the casting wheel, and preprocess the real-time temperature data; Based on the real-time temperature data, a moving average algorithm is used to determine the temperature information value of each monitoring point. The temperature information value includes the average temperature within a set time interval and the standard deviation and range between each monitoring point. The temperature information values ​​of each monitoring point are collected, summarized, and assigned to the overall analysis signal.

3. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 2, characterized in that, The formation process of the local analysis signal includes the following steps: The surface and inner space of the casting wheel are divided into local areas, and each local area includes at least one monitoring point. Real-time temperature data in each local area are determined in turn. Using the real-time temperature data, temperature characteristic values ​​are determined sequentially for each local region, including the highest temperature, the lowest temperature, and the temperature gradient. The temperature characteristic values ​​of each local area are collected and summarized and assigned as local analysis signals.

4. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 3, characterized in that, The formation process of the change analysis signal includes the following steps: Collect real-time temperature data from various monitoring points on the casting wheel at continuous time points to form a temperature time series; The temperature change rate under the temperature time series of each monitoring point is calculated using the finite difference method to obtain the temperature change rate series of each point. The temperature change rate sequence of each monitoring point is compiled and summarized and assigned as a change analysis signal.

5. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 4, characterized in that, The formation process of the anomaly analysis signal includes the following steps: Real-time temperature data of each monitoring point of the casting wheel is acquired, and a score conversion algorithm based on machine learning is used to calculate the effective score corresponding to each real-time temperature data and determine whether it exceeds the confidence interval of the normal range. When the data exceeds the confidence interval, the monitoring point corresponding to the real-time temperature data is determined to be an anomaly. The temperature data features of the anomaly point and its adjacent distributed monitoring points are extracted, and the anomaly feature information is obtained by extracting and analyzing the temperature data features. The abnormal feature information is collected and summarized and assigned as an abnormal analysis signal.

6. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 1, characterized in that, The analyzed signals are prioritized, with priority features inserted for each signal. The signals are then sorted and reorganized to form a signal dataset. Includes the following steps: Within the same unit time interval, at least four priority features are set, and their levels are arranged sequentially from the zeroth priority. The initial priority features of the overall analysis signal, the local analysis signal, and the change analysis signal are assigned to the third priority, and the initial priority feature of the anomaly analysis signal is assigned to the first priority. Construct correlation feature rules between different analysis signals, and when the correlation feature rules are triggered, perform correlation marking between the related analysis signals; Based on the differences between the information data contained in each analysis signal and the confidence intervals of the fluctuation range and the duration range, and combined with the results of the correlation feature determination, the priority features of the current analysis signal and the associated analysis signals are determined to be either increased, maintained, or decreased. Based on the priority characteristics of the analyzed signals, priority characteristics are reassigned to the analyzed signals sequentially from the zeroth priority, and the recombined signals form a signal dataset.

7. The temperature monitoring and communication control system for the continuous casting process of copper rods according to claim 6, characterized in that, The step of extracting keyframe information from each analyzed signal in the signal dataset and determining whether the analyzed signal should be output as a target signal to the information processing module based on the priority feature includes the following steps: The analysis signal corresponding to the zeroth priority in the information dataset is selected, and the analysis signals corresponding to the other priority features are retained as reference signals. Capture key frame information of the current analysis signal and construct a key frame feature vector containing timestamps. The key frame information includes any one of temperature information values, temperature feature values, temperature change rate sequences, or abnormal feature information. Based on the data format and communication protocol, the current analysis signal and its corresponding key frame feature vector are output as target signals to the information processing module, while the analysis signal corresponding to the next priority feature is extracted as a candidate signal. Repeat the above steps until every analyzed signal and its corresponding keyframe feature vector in the signal dataset are sent to the information processing module.

8. A method for temperature monitoring and communication control in the continuous casting process of copper rods, using the temperature monitoring and communication control system for the continuous casting process of copper rods as described in any one of claims 1 to 7, characterized in that, Includes the following steps: The information acquisition module acquires several real-time temperature data of the casting wheel during the continuous casting process of copper rod; The signal acquisition unit generates analysis signals, which include overall analysis signals, local analysis signals, change analysis signals, and anomaly analysis signals. The signal processing unit performs priority processing on the analyzed signals, inserts priority features into each analyzed signal, and sorts and reassembles them to form a signal dataset. The signal determination unit captures keyframe information for each analyzed signal in the signal dataset and determines whether the analyzed signal should be output as a target signal to the information processing module based on the priority feature. The information processing module receives the target signal, performs corresponding analysis and processing steps based on the target signal, and outputs a status analysis report corresponding to the target signal of the casting wheel. The information control module generates improvement instructions based on the status analysis report and interacts with external devices through the information communication module to form improvement instruction exchanges.

9. A temperature monitoring and communication control device for a copper rod continuous casting process, using the temperature monitoring and communication control system for a copper rod continuous casting process as described in any one of claims 1 to 7, characterized in that, include: The housing includes a plurality of temperature sensors, a temperature recorder, and an energy storage device built into the housing. The sensing ends of the temperature sensors are led out from the openings in the housing and are respectively sealed and mounted at set points on the casting wheel. The temperature recorder is communicatively connected to each of the temperature sensors to read and record each real-time temperature data. The energy storage device is used to supply energy to the temperature sensors and the temperature recorder.

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