An intelligent safety control system for one-button pulverizing of coal injection in ironmaking

Abstract

The present invention discloses a one-button intelligent safety control system for coal-injection powder making in iron smelting, including a monitoring acquisition module, a communication transmission module, a data preprocessing and analysis module, an early warning transmission module, an execution unit and a user visualization interface, and the present invention relates to the technical field of coal-injection powder making safety control. The one-button intelligent safety control system for coal-injection powder making in iron smelting, by receiving data and implementing classification processing operations, establishes a simulation analysis model related to powder making and powder injection, and predicts the risk of the powder making process based on the oxygen content curve formed during powder making according to the data, and predicts the risk of the coal powder storage process based on the coal injection amount and the rate of the powder making amount, thereby realizing a one-button intelligent powder making control operation, which not only effectively improves the efficiency of powder making, but also can predict safety risks in advance, improve the fault tolerance rate in operation, and also can realize the discovery and solution of fault problems, and realize safe and intelligent powder making control operation.

Description

Technical Field

[0001] The invention relates to the technical field of coal injection pulverizing safety control, and in particular to an ironmaking coal injection one-button pulverizing intelligent safety control system. Background Art

[0002] The reference patent name is: Ironmaking Coal Injection One-button Pulverizing Intelligent Safety Control System (Patent Publication Number: CN116736788A, Patent Publication Date: 2023-09-12), including an upper computer HMI monitoring system and a lower computer PLC control system. The data processing block of the PLC control system compares and processes the real-time data collected by the instrument data acquisition block with the safety parameters of each instrument initially set by the operator to form A-level warning, B-level warning and C-level alarm fault shutdown outputs to achieve safe control of the coal injection and pulverizing system. The intelligent safety warning control is divided into three types of warning signals: A-level warning, B-level warning and C-level alarm fault shutdown. The system will shut down intelligently. In addition, if the oxygen content is out of control, the system will shut down intelligently to avoid the system from being in a negative pressure state and causing accidents to become more serious, which is suitable for wide promotion.

[0003] Based on the description in the above-mentioned documents, although the existing one-key pulverizing operation for coal injection in iron smelting can meet the real-time operation of pulverizing and coal injection, in actual application, it fails to monitor and control the oxygen content and the amount of stored coal powder in real time, so that in the continuous pulverizing and coal injection operation, there is a problem of excessive oxygen content or excessive storage of coal powder, resulting in the risk of spontaneous combustion or even explosion, and it fails to make timely predictions and controls for safety issues. For this reason, the present invention provides a one-key pulverizing intelligent safety control system for coal injection in iron smelting. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent safety control system for one-key pulverizing of coal injection in ironmaking, which solves the problem that in the existing one-key pulverizing operation of coal injection in ironmaking, although the real-time operation of pulverizing and coal injection can be met, in practical application, the oxygen content and the amount of stored coal powder cannot be monitored and controlled in real time, so that in the continuous pulverizing and coal injection operations, there is a problem of excessive oxygen content or excessive storage of coal powder, resulting in the risk of spontaneous combustion or even explosion, and timely prediction and control of safety issues cannot be made.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent safety control system for one-key pulverizing of coal injection for ironmaking, comprising:

[0006] Monitoring and acquisition module, used to monitor various parameters in the powder making and powder spraying process in real time, and realize data transmission and storage;

[0007] Communication transmission module, which realizes the transmission operation of collected data through wireless communication technology;

[0008] The data preprocessing and analysis module receives data and implements classification processing operations, establishes a simulation analysis model related to pulverizing and powder injection, forms an oxygen content curve during pulverizing based on the data to predict the risk of the pulverizing process, predicts the risk of the pulverized coal storage process based on the coal injection amount, the pulverizing rate and the combination, and transmits the predicted results;

[0009] The early warning transmission module receives the prediction results, generates early warning signals and immediately generates instructions to send to the execution unit;

[0010] The execution unit realizes the adjustment operation of the opening and closing switches of the corresponding equipment or the pipeline valves according to the received instructions;

[0011] The user visualization interface displays the collected and processed data, warning signals and execution instructions, and personnel can confirm and issue adjustment instructions through touch screen control.

[0012] Preferably, the operations of receiving data and implementing classification processing in the data preprocessing and analysis module are:

[0013] A1. Extract the title content of the data required subsequently, and form the identification sequence of each data set according to the title content, marked as M;

[0014] A2, identifying and matching the received data with the identification sequence M, and dividing the data in sequence to form the identification sequence M with the data;

[0015] A3. Finally, the data in each identification sequence M is extracted and classified into a historical data set labeled G, an oxygen content data set labeled H, and an operating parameter data set labeled K.

[0016] Preferably, the expression for data identification and matching in A2 is:

[0017] ;

[0018] m represents the received collected data, M represents the identification sequence of each item, G represents the historical data set of pulverizing and coal injection, H represents the oxygen content data set during pulverizing, and K represents the operating parameter data set of pulverizing and coal injection. Represents the automatic generation of data into a dataset.

[0019] Preferably, the operation of establishing a simulation analysis model associated with powder making and powder spraying in the data preprocessing and analysis module is:

[0020] B1. Extract basic data for model establishment based on historical data set G, so as to realize the operation instruction association operation of ironmaking coal injection equipment and one-key pulverizing equipment;

[0021] B2. Then extract the various safety threshold data in the historical data set G and introduce them into the model to establish the required simulation analysis model.

[0022] Preferably, the step of forming an oxygen content curve during milling by data in the data preprocessing and analysis module to predict the risk of the milling process is:

[0023] C1, by introducing the oxygen content data set H into the simulation analysis model, and extracting the measured oxygen content concentration values ​​in chronological order;

[0024] C2. Input the time nodes and oxygen content concentration values ​​in sequence to establish an oxygen content curve, and then find the risk time node according to the risk threshold and the prediction node threshold and the oxygen content concentration, and then generate risk feedback instructions according to the risk time node;

[0025] C3. Implement control operations of the unit according to the risk feedback instructions, and implement oxygen content detection operations in real time according to the control operations.

[0026] Preferably, the operation of establishing the oxygen content curve and finding the risk time node in C2 is:

[0027] c21. The collected time nodes are used as the horizontal axis of the curve coordinates, and the oxygen content concentration values ​​at the corresponding time nodes are used as the vertical axis of the curve coordinates, and the horizontal axis intersects with the starting point of the vertical axis;

[0028] c22. Starting from the starting point, the corresponding data nodes are added in sequence, and the data nodes are connected in sequence to form a curve, and the state of the curve is determined according to the change trend of adjacent data nodes;

[0029] Set the coordinates of the previous data node to P (x1, y1), and the coordinates of the subsequent data node to Q (x2, y2), where x2>x1, if y1<y2, then the curve is an ascending curve, otherwise, if y2<y1, then the curve is a descending curve;

[0030] c23. Then, according to the prediction node threshold, a constant function Y=j is introduced, where j is the value of the prediction node threshold, and the constant function is compared with the value of the curve;

[0031] When the curve is an ascending curve, and y max When y < j, real-time monitoring and comparison will continue. max ≥j, the data node corresponding to the current time node is the risk time node;

[0032] When the curve is a descending curve, and y max When y < j, real-time monitoring and comparison will continue. max≥j, the data node corresponding to the current time node is the risk time node, and until y max drops to less than j.

[0033] Preferably, the expression of the risk time node in c23 is:

[0034] F = (x n ,y n ) = (x n ,y max ), y n >y n-1 ,y max ≥j;

[0035] F represents the coordinates of the corresponding risk time node, and x n is the nth time node, y n Indicates the oxygen content value corresponding to the nth time node, and while satisfying the rising curve, y n With y max The values ​​of y are the same, but max When it is greater than or equal to the prediction node threshold j, that is, the current time node and oxygen content value correspond to the coordinate value on the curve, and it is a risk time node.

[0036] Preferably, the steps of predicting the risk of the pulverized coal storage process in the data preprocessing and analysis module based on the rate of coal injection amount and pulverizing amount are as follows:

[0037] D1, introduce the operating parameter data set K into the simulation analysis model, and extract the set coal injection rate as V1, the set pulverizing rate as V2, and the required coal powder injection quantity W;

[0038] D2. Then, the storage data of the pulverized coal storage bin is analyzed. The storage height of the pulverized coal is measured by a sensor located at the feed point inside the pulverized coal storage bin, which is marked as h. The length and width of the pulverized coal storage bin are L1 and L2.

[0039] D3. The set safety storage volume threshold is R, and the set storage volume threshold when the pulverizing process is started is S, and the time to stop pulverizing process is calculated based on the coal injection rate V1 and the pulverizing rate V2.

[0040] Preferably, the calculation formula for stopping the milling time in D3 is:

[0041] The time of using pulverized coal is: ;

[0042] The milling operation is started after the time t is met, and the time from the start of milling to the stop is:

[0043] ;

[0044] The milling operation is stopped after the milling time T is started.

[0045] Preferably, the operations of generating a warning signal and executing instructions according to the prediction results in the warning transmission module are:

[0046] E1, that is, when the data node corresponding to the current time node in c23 is a risk time node, a warning signal of excessive oxygen content is generated, and a command signal for reducing the oxygen content is generated to implement the control operation of the execution unit;

[0047] E2, that is, when the current pulverized coal storage amount in D3 drops to the storage amount threshold S, a warning signal of low pulverized coal storage amount is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the startup operation. Then, while satisfying the coal injection operation, until the pulverized coal storage amount rises to the safety storage amount threshold R, a warning signal of pulverized coal storage amount reaching the standard is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the shutdown operation.

[0048] The present invention provides an intelligent safety control system for one-key coal-injection pulverizing in ironmaking. Compared with the prior art, it has the following beneficial effects:

[0049] (1) The one-button intelligent safety control system for coal injection in ironmaking receives data and implements classification processing operations, establishes a simulation analysis model related to powder making and powder injection, forms an oxygen content curve during powder making based on the data to predict the risk of the powder making process, and predicts the risk of the coal powder storage process based on the coal injection rate and the rate of powder making, thereby realizing one-button intelligent powder making control operation, which not only effectively improves the efficiency of powder making, but also can predict safety risks in advance and improve the fault tolerance rate in operation. At the same time, it can also realize the discovery and solution of fault problems, and realize safe and intelligent powder making control operation.

[0050] (2) The one-button pulverizing intelligent safety control system for ironmaking coal injection introduces the oxygen content data set into the simulation analysis model, inputs the time node and oxygen content concentration values ​​in sequence to establish the oxygen content curve, and then finds the risk time node based on the risk threshold and the prediction node threshold and the oxygen content concentration. Then, the risk feedback instruction is generated according to the risk time node, so that the data can be monitored in real time while the risk avoidance is carried out in advance according to the data. If there is a problem with the equipment, it can be discovered and solved in time, rather than discovered after exceeding the safety threshold, thereby improving the fault tolerance rate and making the reliability and stability of the safety control system.

[0051] (3) The one-button intelligent safety control system for coal injection in ironmaking introduces the operating parameter data set into the simulation analysis model. According to the real-time coal injection powder demand, the coal injection rate, the powder making rate and the storage amount are combined to calculate the time to stop the powder making operation. This can realize the linkage of various influences, effectively control the storage amount, reduce safety risks and avoid the exhaustion of the stored coal injection powder. In this way, intelligent management and control can improve production efficiency, simultaneously improve safety control effects, and accurately control the operation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] FIG1 is a functional block diagram of a safety control system of the present invention;

[0053] FIG2 is a flow chart of the classification processing operation of the data preprocessing and analysis module of the present invention;

[0054] FIG3 is a flowchart of the oxygen content analysis operation of the data preprocessing and analysis module of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Please refer to Figures 1 to 3. The present invention provides a technical solution: an intelligent safety control system for one-key pulverizing of coal injection for ironmaking, comprising:

[0057] Monitoring and acquisition module, used to monitor various parameters in the powder making and powder spraying process in real time, and realize data transmission and storage;

[0058] Communication transmission module, which realizes the transmission operation of collected data through wireless communication technology;

[0059] The data preprocessing and analysis module receives data and implements classification processing operations, establishes a simulation analysis model related to pulverizing and powder injection, forms an oxygen content curve during pulverizing based on the data to predict the risk of the pulverizing process, predicts the risk of the pulverized coal storage process based on the coal injection amount, the pulverizing rate and the combination, and transmits the predicted results;

[0060] The early warning transmission module receives the prediction results, generates early warning signals and immediately generates instructions to send to the execution unit;

[0061] The execution unit realizes the adjustment operation of the opening and closing switches of the corresponding equipment or the pipeline valves according to the received instructions;

[0062] The user visualization interface displays the collected and processed data, warning signals and execution instructions, and personnel can confirm and issue adjustment instructions through touch screen control.

[0063] The monitoring and acquisition module contains various types of sensor devices, which are used to monitor various parameters in the milling process in real time, such as temperature, pressure, flow, etc.

[0064] Among them, by receiving data and implementing classification processing operations, a simulation analysis model related to powder making and powder injection is established, and the oxygen content curve during powder making is formed according to the data to predict the risk of the powder making process. The risk of the coal powder storage process is predicted based on the rate of coal injection and powder making, so as to realize one-click intelligent powder making control operation, which not only effectively improves the efficiency of powder making, but also can predict safety risks in advance and improve the fault tolerance rate in operation. At the same time, it can also realize the discovery and solution of fault problems and realize safe and intelligent powder making control operation.

[0065] In the embodiment of the present invention, the operations of receiving data and implementing classification processing in the data preprocessing and analysis module are:

[0066] A1. Extract the title content of the data required subsequently, and form the identification sequence of each data set according to the title content, marked as M;

[0067] A2, identifying and matching the received data with the identification sequence M, and dividing the data in sequence to form the identification sequence M with the data;

[0068] A3. Finally, the data in each identification sequence M is extracted and classified into a historical data set labeled G, an oxygen content data set labeled H, and an operating parameter data set labeled K.

[0069] In the embodiment of the present invention, the expression for data identification and matching in A2 is:

[0070] ;

[0071] m represents the received collected data, M represents the identification sequence of each item, G represents the historical data set of pulverizing and coal injection, H represents the oxygen content data set during pulverizing, and K represents the operating parameter data set of pulverizing and coal injection. Represents the automatic generation of data into a dataset.

[0072] In the embodiment of the present invention, the operation of establishing a simulation analysis model associated with powder making and powder spraying in the data preprocessing and analysis module is as follows:

[0073] B1. Extract basic data for model establishment based on historical data set G, so as to realize the operation instruction association operation of ironmaking coal injection equipment and one-key pulverizing equipment;

[0074] B2. Then extract the various safety threshold data in the historical data set G and introduce them into the model to establish the required simulation analysis model.

[0075] In the embodiment of the present invention, the steps of forming an oxygen content curve during milling by data in the data preprocessing and analysis module to predict the risk of the milling process are as follows:

[0076] C1, by introducing the oxygen content data set H into the simulation analysis model, and extracting the measured oxygen content concentration values ​​in chronological order;

[0077] C2. Input the time nodes and oxygen content concentration values ​​in sequence to establish an oxygen content curve, and then find the risk time node according to the risk threshold and the prediction node threshold and the oxygen content concentration, and then generate risk feedback instructions according to the risk time node;

[0078] C3. Implement control operations of the unit according to the risk feedback instructions, and implement oxygen content detection operations in real time according to the control operations.

[0079] Among them, by introducing the oxygen content data set into the simulation analysis model, the time nodes and oxygen content concentration values ​​are input in turn to establish the oxygen content curve, and then the risk time node is found according to the risk threshold and the prediction node threshold and the oxygen content concentration. Then, the risk feedback instruction is generated according to the risk time node, so that the data can be monitored in real time while the risk avoidance is carried out in advance according to the data. If there is a problem with the equipment, it can be discovered and solved in time, rather than discovered after exceeding the safety threshold, which improves the fault tolerance rate and makes the reliability and stability of the safety control system.

[0080] In the embodiment of the present invention, the operation of establishing the oxygen content curve and finding the risk time node in C2 is:

[0081] c21. The collected time nodes are used as the horizontal axis of the curve coordinates, and the oxygen content concentration values ​​at the corresponding time nodes are used as the vertical axis of the curve coordinates, and the horizontal axis intersects with the starting point of the vertical axis;

[0082] c22. Starting from the starting point, the corresponding data nodes are added in sequence, and the data nodes are connected in sequence to form a curve, and the state of the curve is determined according to the change trend of adjacent data nodes;

[0083] Set the coordinates of the previous data node to P (x1, y1), and the coordinates of the subsequent data node to Q (x2, y2), where x2>x1, if y1<y2, then the curve is an ascending curve, otherwise, if y2<y1, then the curve is a descending curve;

[0084] c23. Then, according to the prediction node threshold, a constant function Y=j is introduced, where j is the value of the prediction node threshold, and the constant function is compared with the value of the curve;

[0085] When the curve is an ascending curve, and y max When y < j, real-time monitoring and comparison will continue. max ≥j, the data node corresponding to the current time node is the risk time node;

[0086] When the curve is a descending curve, and y max When y < j, real-time monitoring and comparison will continue. max ≥j, the data node corresponding to the current time node is the risk time node, and until y max drops to less than j.

[0087] Among them, the safety oxygen content threshold of the coal powder bin in the prior art needs to be less than or equal to 8%, and through the actual monitoring process, the real-time data specific results are shown in Table 1:

[0088] Table 1 Real-time data table

[0089] Time Node 0 2min 4min 6min … Oxygen content 6.5% 6.9% 7.3% 7.6% …

[0090] The prediction node threshold j=7.5% is set in the system, and according to the real-time data table, it can be known that in the cycle time record, the curve of the interval [0, 6] is an upward curve, and y max =7.6%, and after comparison, y max ≥j, so the current risk time node coordinates are (6, 7.6%);

[0091] That is, when experiencing a risk time node, a warning signal of excessive oxygen content is generated, and a command signal to reduce the oxygen content is generated to implement the control operation of the unit, thereby reducing the oxygen content to below 7.5%, effectively avoiding risks.

[0092] In the embodiment of the present invention, the expression of the risk time node in c23 is:

[0093] F = (x n ,y n ) = (x n ,y max ), y n >y n-1 ,y max ≥j;

[0094] F represents the coordinates of the corresponding risk time node, and x n is the nth time node, y n Indicates the oxygen content value corresponding to the nth time node, and while satisfying the rising curve, y n With y max The values ​​of y are the same, but maxWhen it is greater than or equal to the prediction node threshold j, that is, the current time node and oxygen content value correspond to the coordinate value on the curve, and it is a risk time node.

[0095] In the embodiment of the present invention, the steps of predicting the risk of the pulverized coal storage process in the data preprocessing and analysis module based on the rate of coal injection amount and pulverizing amount are as follows:

[0096] D1, introduce the operating parameter data set K into the simulation analysis model, and extract the set coal injection rate as V1, the set pulverizing rate as V2, and the required coal powder injection quantity W;

[0097] D2. Then, the storage data of the pulverized coal storage bin is analyzed. The storage height of the pulverized coal is measured by a sensor located at the feed point inside the pulverized coal storage bin, which is marked as h. The length and width of the pulverized coal storage bin are L1 and L2.

[0098] D3. The set safety storage volume threshold is R, and the set storage volume threshold when the pulverizing process is started is S, and the time to stop pulverizing process is calculated based on the coal injection rate V1 and the pulverizing rate V2.

[0099] Among them, by introducing the operating parameter data set into the simulation analysis model, according to the real-time coal powder injection demand, the time to stop the powder making operation is calculated based on the coal injection rate, the powder making rate and the storage amount, so as to realize the linkage combination of various influences, effectively control the storage amount, reduce safety risks and avoid the depletion of stored coal powder, so as to improve production efficiency through intelligent management and control, simultaneously improve safety control effects, and accurately control the operation time.

[0100] In the embodiment of the present invention, the calculation formula for the time of stopping milling in D3 is:

[0101] The time of using pulverized coal is: ;

[0102] The milling operation is started after the time t is met, and the time from the start of milling to the stop is:

[0103] ;

[0104] The milling operation is stopped after the milling time T is started.

[0105] Among them, in the prior art, the storage capacity of the coal powder bin needs to be less than or equal to 4 hours. Therefore, in the actual monitoring process, the required powder making time is strictly controlled during the production operation according to the corresponding order requirements, and when calculating the storage capacity of the beautiful seam, the sensor is located directly below the feed point. Therefore, the measured coal powder height is actually the highest point of the coal powder in the coal powder storage bin, and the coal powder amount calculated according to L1L2h is greater than the actual coal powder amount, thereby improving the fault tolerance rate.

[0106] In the embodiment of the present invention, the operation of generating a warning signal and executing an instruction according to the prediction result in the warning transmission module is:

[0107] E1, that is, when the data node corresponding to the current time node in c23 is a risk time node, a warning signal of excessive oxygen content is generated, and a command signal for reducing the oxygen content is generated to implement the control operation of the execution unit;

[0108] E2, that is, when the current pulverized coal storage amount in D3 drops to the storage amount threshold S, a warning signal of low pulverized coal storage amount is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the startup operation. Then, while satisfying the coal injection operation, until the pulverized coal storage amount rises to the safety storage amount threshold R, a warning signal of pulverized coal storage amount reaching the standard is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the shutdown operation.

[0109] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0110] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0111] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent safety control system for one-button pulverizing of coal for ironmaking, characterized by: include: Monitoring and acquisition module, used to monitor various parameters in the powder making and powder spraying process in real time, and realize data transmission and storage; Communication transmission module, which realizes the transmission operation of collected data through wireless communication technology; The data preprocessing and analysis module receives data and implements classification processing operations, establishes a simulation analysis model related to pulverizing and powder injection, forms an oxygen content curve during pulverizing based on the data to predict the risk of the pulverizing process, predicts the risk of the pulverized coal storage process based on the coal injection amount, the pulverizing rate and the combination, and transmits the predicted results; The early warning transmission module receives the prediction results, generates early warning signals and immediately generates instructions to send to the execution unit; The execution unit realizes the adjustment operation of the opening and closing switches of the corresponding equipment or the pipeline valves according to the received instructions; The user visualization interface displays the collected and processed data, warning signals and execution instructions, and personnel can confirm and issue adjustment instructions through touch screen control; The operations of receiving data and implementing classification processing in the data preprocessing and analysis module are: A1. Extract the title content of the data required subsequently, and form the identification sequence of each data set according to the title content, marked as M; A2, identifying and matching the received data with the identification sequence M, and dividing the data in sequence to form the identification sequence M with the data; A3. Finally, the data in each identification sequence M is extracted and classified into a historical data set labeled G, an oxygen content data set labeled H, and an operating parameter data set labeled K; The steps in the data preprocessing and analysis module based on the rate of coal injection amount and pulverizing amount combined with the prediction of the risk of coal pulverized storage process are as follows: D1, introduce the operating parameter data set K into the simulation analysis model, and extract the set coal injection rate as V1, the set pulverizing rate as V2, and the required coal powder injection quantity W; D2. Then, the storage data of the pulverized coal storage bin is analyzed. The storage height of the pulverized coal is measured by a sensor located at the feed point inside the pulverized coal storage bin, which is marked as h. The length and width of the pulverized coal storage bin are L1 and L2. D3, the safety storage volume threshold is set as R, and the storage volume threshold when the pulverizing is started is set as S, and the time to stop pulverizing is calculated based on the coal injection rate V1 and the pulverizing rate V2; The calculation formula for the time of stopping milling in D3 is: The time of using pulverized coal is: ; and the milling operation is started after the time t is met, and the time from the start of milling to the stop is: The milling operation is stopped after the milling time T is started.

2. According to claim 1, a one-button pulverizing intelligent safety control system for ironmaking coal injection is characterized in that: The expression for data identification and matching in A2 is: ; m represents the received collected data, M represents the identification sequence of each item, G represents the historical data set of pulverizing and coal injection, H represents the oxygen content data set during pulverizing, and K represents the operating parameter data set of pulverizing and coal injection. Represents the automatic generation of data into a dataset.

3. The one-key coal-injection pulverizing intelligent safety control system for ironmaking according to claim 1 is characterized in that: The operation of establishing a simulation analysis model associated with powder making and powder spraying in the data preprocessing and analysis module is as follows: B1. Extract basic data for model establishment based on historical data set G, so as to realize the operation instruction association operation of ironmaking coal injection equipment and one-key pulverizing equipment; B2. Then extract the various safety threshold data in the historical data set G and introduce them into the model to establish the required simulation analysis model.

4. The one-key coal-injection pulverizing intelligent safety control system for ironmaking according to claim 1 is characterized in that: The steps of forming the oxygen content curve during milling by the data preprocessing and analysis module to predict the risk of the milling process are as follows: C1, by introducing the oxygen content data set H into the simulation analysis model, and extracting the measured oxygen content concentration values ​​in chronological order; C2. Input the time nodes and oxygen content concentration values ​​in sequence to establish an oxygen content curve, and then find the risk time node according to the risk threshold and the prediction node threshold and the oxygen content concentration, and then generate risk feedback instructions according to the risk time node; C3. Implement control operations of the unit according to the risk feedback instructions, and implement oxygen content detection operations in real time according to the control operations.

5. The one-key coal-injection pulverizing intelligent safety control system for ironmaking according to claim 4 is characterized in that: The operation of establishing the oxygen content curve and finding the risk time node in C2 is: c21. The collected time nodes are used as the horizontal axis of the curve coordinates, and the oxygen content concentration values ​​at the corresponding time nodes are used as the vertical axis of the curve coordinates, and the horizontal axis intersects with the starting point of the vertical axis; c22. Starting from the starting point, the corresponding data nodes are added in sequence, and the data nodes are connected in sequence to form a curve, and the state of the curve is determined according to the change trend of adjacent data nodes; Set the coordinates of the previous data node to P (x1, y1), and the coordinates of the subsequent data node to Q (x2, y2), where x2>x1, if y1<y2, then the curve is an ascending curve, otherwise, if y2<y1, then the curve is a descending curve; c23. Then, according to the prediction node threshold, a constant function Y=j is introduced, where j is the value of the prediction node threshold, and the constant function is compared with the value of the curve; When the curve is an ascending curve, and y max When y < j, real-time monitoring and comparison will continue. max ≥j, the data node corresponding to the current time node is the risk time node; When the curve is a descending curve, and y max When y < j, real-time monitoring and comparison will continue. max ≥j, the data node corresponding to the current time node is the risk time node, and until y max drops to less than j.

6. The one-key coal-injection pulverizing intelligent safety control system for ironmaking according to claim 5 is characterized by: The expression of the risk time node in c23 is: F=(x n ,and n )=(x n ,and max ),and n >and n-1 ,and max ≥j; F represents the coordinates of the corresponding risk time node, and x n is the nth time node, y n Indicates the oxygen content value corresponding to the nth time node, and while satisfying the rising curve, y n With y max The values ​​of y are the same, but max When it is greater than or equal to the prediction node threshold j, that is, the current time node and oxygen content value correspond to the coordinate value on the curve, and it is a risk time node.

7. The one-key coal-injection pulverizing intelligent safety control system for ironmaking according to claim 5 is characterized by: The operations of generating a warning signal and executing instructions according to the prediction results in the warning transmission module are: E1, that is, when the data node corresponding to the current time node in c23 is a risk time node, a warning signal of excessive oxygen content is generated, and a command signal for reducing the oxygen content is generated to implement the control operation of the execution unit; E2, that is, when the current pulverized coal storage amount in D3 drops to the storage amount threshold S, a warning signal of low pulverized coal storage amount is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the startup operation. Then, while satisfying the coal injection operation, until the pulverized coal storage amount rises to the safety storage amount threshold R, a warning signal of pulverized coal storage amount reaching the standard is generated, and an instruction is generated and transmitted to the pulverizing unit to implement the shutdown operation.

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