Hot blast stove spark edge computing calculation hierarchical response method and cloud platform early warning system

Abstract

The present application relates to the technical field of hot blast stove, and particularly relates to a hot blast stove spark edge computing hierarchical response method and a cloud platform early warning system, the method comprises the following steps: obtaining a spark flow path and equipment information flowing through from a database; constructing a segmented hierarchical early warning strategy, and triggering a corresponding level of warning by real-time positioning of abnormalities at different positions on the spark flow path through edge computing; obtaining a position and level of early warning, identifying movement characteristics and temperature characteristics of the spark to distinguish the composition of the spark, diagnosing a fault type of the hot blast stove according to the composition of the spark, and taking corresponding response measures.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hot blast stove, in particular to a hot blast stove spark edge computing hierarchical response method and a cloud platform early warning system. BACKGROUND

[0002] Hot blast stove has become a replacement product of electric heat source and traditional steam power heat source in many industries, such as providing hot air for crop drying and providing high-temperature combustion-supporting air with sustained temperature for blast furnace. The reasons for the phenomenon of "spark" or "sparkle" generated by hot blast stove are usually as follows:

[0003] 1. Spalling or damage of refractory material. When the particles of the spalled refractory bricks are carried out by high-temperature hot air or waste gas flow, they show "spark" state in the gas flow due to their extremely high temperature (more than 1000℃);

[0004] 2. Incomplete combustion of fuel particles. Due to improper adjustment of the burner (mismatch of air-fuel ratio or poor air distribution), large fluctuation of coal gas pressure / heat value, etc., the fuel particles cannot be fully combusted, forming "spark".

[0005] The movement path of the spark generated by the spalling or damage of refractory material: regenerator checker brick channel to hot air outlet to hot air main to blast furnace tuyere (air supply period). Or regenerator checker brick channel to flue to chimney.

[0006] The movement path of the spark generated by the incomplete combustion of fuel particles: combustion chamber to waste gas valve to flue (mainly at the end of the combustion period, switching to the air supply period or the waste gas discharge period).

[0007] The occurrence of spark in hot blast stove is a fault signal. Especially the spark ejected from the hot blast valve and the flange of the pipeline, which is most likely caused by leakage of the hot blast valve or damage of the pipeline; the dark red spark floating out of the chimney is most likely caused by spalling of refractory material or ash carried by waste gas, which must be checked for faults.

[0008] In reality, professionals usually patrol, make fault judgments and take corresponding treatment schemes in combination with the position and color and shape of the discovered spark. However, the occurrence of these features means that the fault has already occurred. How to monitor the movement state and temperature state of the spark inside the hot blast stove, accurately know the internal state of the system and predict the occurrence of faults to reduce the risk is an urgent problem to be solved. SUMMARY

[0009] According to the nodes of the movement state and temperature state of the spark, the present application divides the movement path of the spark into multiple segments in combination with the key equipment passed through, predicts the average temperature and movement state of the spark in each segment by using edge computing, and performs early warning of different levels by comprehensively considering the size of the risk index.

[0010] The technical solution proposed in this invention is: a hierarchical response method for calculating the Martian edge of a hot blast stove, the method comprising:

[0011] Retrieve Mars's trajectory and the information of the equipment it passes through from the database;

[0012] A segmented and hierarchical early warning strategy is constructed, which uses edge computing to locate anomalies at different locations along the Martian flow path in real time and trigger warnings of the corresponding level.

[0013] The system obtains the location and level of the early warning, identifies the motion and temperature characteristics of Mars to distinguish its composition, diagnoses the fault type of the hot air furnace based on the Martian composition, and takes corresponding response measures.

[0014] Preferably, the construction of the segmented and hierarchical early warning strategy includes:

[0015] The Martian flow path is segmented based on key equipment along the Martian flow path, the inflection points of Martian temperature and Martian velocity, and the potential hazards on Mars.

[0016] The motion, temperature, and shape features of Mars for each segment are obtained. The motion features include the Martian motion velocity vector and acceleration vector; the temperature and shape features include the Martian temperature and shape factor.

[0017] Each segment has three warning levels, including:

[0018] The comprehensive risk index for each segment is calculated using the Martian velocity and average Martian temperature. ;in, They represent the first The segment's temperature weight, speed weight, static risk weight, and specific risk factors; They represent the first Average temperature of Mars, reference temperature, maximum permissible temperature deviation, Mars velocity, reference velocity, and maximum permissible velocity deviation;

[0019] The warning level is determined based on the region where the comprehensive risk index is located, including:

[0020] when It was at the level of Level 1 warning;

[0021] when The alert level is currently Level II.

[0022] when The alert level is currently at Level 3.

[0023] Preferably, the step of using edge computing to locate anomalies at different locations along the Martian flow path in real time and triggering warnings of corresponding levels includes:

[0024] Constructing a Mars trajectory model wherein, respectively represent the position vector, velocity vector, acceleration vector, time step, Gaussian noise term, gas density, Mars particle density, Mars particle diameter, drag coefficient, flow velocity vector and gravitational acceleration vector of Mars at time t;

[0025] Mars temperature decay prediction model wherein, represents the regression coefficient, represents the average temperature of Mars, ambient temperature and gas constant at time t, represents the edge computing LSTM model; represents the standard activation energy;

[0026] According to the Mars trajectory prediction model and the Mars temperature decay prediction model, the Mars is predicted at each segment velocity vector and temperature, the predicted temperature value and the modulus of the velocity vector are taken as input variables, and substituted into , and the comprehensive risk prediction value of each segment is output;

[0027] According to the size of the comprehensive risk prediction value, the corresponding level of warning is output.

[0028] Preferably, the real-time positioning of the abnormal position on the Mars flow path by edge computing and triggering the corresponding level of warning further comprises:

[0029] By constructing a rotating flow field model, the accuracy of Mars trajectory prediction and temperature measurement under rotating airflow is improved, comprising:

[0030] Constructing a three-dimensional vortex field analytical model ; wherein, represents the flow velocity vector, represents the gas pressure, represents the kinematic viscosity, represents the rotational flow angular velocity vector, represents the Coriolis force term;

[0031] The flow velocity vector ; represents the spatial position coordinates of Mars, represents the POD modal function, represents the number of POD modes; time coefficient obtained by inverting the data of the pipe wall surface pressure sensor;

[0032] Optimizing the acceleration vector in the Mars motion trajectory model, adding a virtual mass force term: ; wherein, represents the velocity vector of the Mars particles, represents the particle density; represents the derivative of the fluid substance; ;

[0033] obtain the accurate position of Mars by solving the updated Mars motion trajectory model through the extended Kalman filter;

[0034] construct a radiation transmission correction model to correct the temperature measurement error caused by the fly ash in the flue gas affecting the radiation coefficient; including:

[0035] the real temperature of Mars , wherein, represents the measured temperature of the infrared temperature measuring instrument or the predicted temperature of the Mars temperature attenuation prediction model, represents the fly ash absorption coefficient; represents the fly ash concentration; represents the radiation propagation path, represents the path integral unit;

[0036] construct a dynamic response compensation model to compensate for the dynamic response delay caused by the thermal inertia of the thermocouple, causing the delay of temperature measurement; including:

[0037] thermocouple response model ;

[0038] measurement lag caused by thermal inertia of thermocouple ; wherein, represents the real gas temperature, the thermocouple strategy temperature and the thermal response time at the moment;

[0039] then, the final temperature after compensation is ;

[0040] recalculate the comprehensive risk index based on the supplemented final temperature, and output different levels of early warning according to the size of the recalculated risk index.

[0041] Preferably, before outputting the corresponding level of early warning according to the size of the comprehensive risk prediction value, it further includes:

[0042] evaluate the processing effect of the upstream section on Mars, including:

[0043] obtain the number of Mars at the inlet and outlet of the section , calculate the Mars capture efficiency ;

[0044] obtain the temperature of Mars at the inlet and outlet of the section , calculate the Mars cooling efficiency ;

[0045] obtain the velocity vector of Mars at the inlet and outlet of the section , calculate the efficiency of the speed reduction of the Mars ;

[0046] Obtain the segmented inlet and outlet Mars flow , calculate the residual flux of the Mars ;

[0047] Build a qualified judgment function:

[0048] ; wherein, The Heaviside step function is represented by H, ; The Mars capture rate threshold, the temperature reduction efficiency threshold, the speed reduction efficiency threshold, and the residual flux threshold are represented by

[0049] If the value of the qualified judgment function of the segment is greater than the preset qualified threshold, it is determined that the Mars treatment effect of the segment is qualified; otherwise, it is unqualified.

[0050] Preferably, before outputting the corresponding level of early warning according to the size of the comprehensive risk prediction value, it further comprises:

[0051] Determine whether the abnormal upstream segment parameters will cause false alarm of the downstream segment;

[0052] Quantify the influence of the abnormal upstream segment parameters on the downstream monitoring.

[0053] Build an upstream and downstream influence analysis model, comprising:

[0054] Build a transfer equation of temperature and speed ; wherein, The real temperature passing through the Mars is calculated at this time;

[0055] Build a constraint equation of temperature and speed ; wherein, the temperature safety margin is , the speed safety margin is ; The downstream temperature alarm threshold and the downstream speed alarm threshold are represented by The temperature safety factor and the speed safety factor are represented by The Mars speed under the rated operating condition of the downstream segment is represented by

[0056] Couple the transfer matrix in , the temperature self-transfer coefficient, the temperature influence coefficient on speed, the speed influence coefficient on temperature, and the speed self-transfer coefficient are represented by

[0057] The Mars temperature safety range in the segment is , wherein, ;

[0058] The safe range of the upstream segment is wherein, ;

[0059] If the change range of the upstream abnormal parameter is within the temperature safe range and the speed safe range, it is determined that the abnormality of the upstream parameter will not cause false alarm of the downstream;

[0060] Quantifying the influence of the upstream segment abnormal parameter change on the downstream monitoring includes:

[0061] Setting a temperature influence index , and a speed influence index ;

[0062] Obtaining a comprehensive influence degree ; wherein, respectively represent the temperature influence weight and the speed influence weight, represents the average temperature of the downstream segment under the rated working condition;

[0063] If , it is determined that the influence degree on the downstream is level one;

[0064] If , it is determined that the influence degree on the downstream is level two;

[0065] If , it is determined that the influence degree on the downstream is level three;

[0066] If , it is determined that the influence degree on the downstream is level four.

[0067] Preferably, the obtaining of the early warning position and level, the identification of the movement characteristics and the temperature characteristics of the star to distinguish the composition of the star, the diagnosis of the fault type of the hot blast furnace according to the composition of the star, and the taking of the corresponding response measures include:

[0068] Obtaining the early warning level of the corresponding segment, if it is a level three early warning, obtaining the real-time data stream of the corresponding segment, extracting the inertia characteristic index feature , the temperature decay factor , and the radiation spectrum entropy to form an input feature vector;

[0069] Inputting the input feature vector into a pre-trained classification decision tree model to output the type of the star particle; the type of the star particle includes refractory brick particles and unburned fuel particles;

[0070] According to the output type of the star particle, performing re-combustion feature detection includes:

[0071] acquiring the temperature of the spark particles, the oxygen concentration, the activation energy of the particles and the time of the spark particles flowing through the segment in the current segment;

[0072] calculating the spark particle reignition probability ; wherein, represents the ignition temperature of the particles and the oxygen concentration, represents the time of the spark particles flowing through the segment, respectively represent the temperature change weight coefficient, the environment weight coefficient and the time weight coefficient;

[0073] If , it indicates that the particles will not reignite;

[0074] If , it indicates that the particles will reignite;

[0075] If , it indicates that the particles have the possibility of reignition;

[0076] Combined with the reignition probability, the type of spark particles is determined, that is:

[0077] If and and , it is judged that the spark particles in the current segment are refractory brick particles, and the fault type is refractory brick fault;

[0078] If and , it is judged that the spark particles in the current segment are unburned fuel particles, and the fault type is insufficient combustion;

[0079] If and or or , it is judged that the spark particles in the current segment are a mixture of fuel particles and refractory brick particles, and the fault type is refractory brick fault and combustion fault;

[0080] According to the fault type and the segment where it is located, a hierarchical response is performed.

[0081] The application also provides a hot blast furnace spark edge calculation hierarchical response cloud platform early warning system, comprising a plurality of edge calculation units and a communication module connected with the edge calculation units, and the system is used for executing the hot blast furnace spark edge calculation hierarchical response method.

[0082] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the hot blast furnace spark edge calculation hierarchical response method.

[0083] The application has the following beneficial effects:

[0084] 1、The present application divides the movement path of Mars into multiple segments, monitors the movement state and temperature state of Mars through edge computing, and judges whether the segment has a fault risk according to the average temperature and speed of Mars in the segment, that is, triggers different levels of early warning through the size of the comprehensive risk index.

[0085] 2、In the present application, when monitoring the movement state and temperature state of Mars, the composition of Mars (refractory brick particles and incompletely burned fuel particles) can be distinguished, so as to identify the fault type and take different measures. BRIEF DESCRIPTION OF DRAWINGS

[0086] Figure 1 The flow chart of the hot blast stove Mars edge computing hierarchical response method of the present application. DETAILED DESCRIPTION

[0087] The following description is used to disclose the present application so that those skilled in the art can implement the present application. The preferred embodiments in the following description are only as examples, and other obvious modifications can be thought of by those skilled in the art. The basic principles of the present application defined in the following description can be applied to other embodiments, modifications, improvements, equivalents and other technical solutions without departing from the spirit and scope of the present application.

[0088] It can be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of one element can be one, and in another embodiment, the number of the element can be multiple, and the term "one" cannot be understood as a limitation on the number.

[0089] Embodiment one:

[0090] Reference Figure 1 The technical solution provided by the present application is: a hot blast stove Mars edge computing hierarchical response method, comprising the following steps:

[0091] Step 1, obtain the Mars flow path and equipment information from the database;

[0092] Step 2, construct a segmented hierarchical early warning strategy, and trigger the corresponding level of warning by real-time positioning of the abnormality at different positions on the Mars flow path through edge computing;

[0093] Among them, the construction of segmented hierarchical early warning strategy includes the following steps:

[0094] The Mars flow path is segmented with the key equipment on the Mars flow path, the Mars temperature and Mars speed inflection point, and the potential hazard degree of Mars as the boundary; for example, in this embodiment, the Mars motion path is divided into 7 segments: the first segment is the combustion injection segment, from the burner outlet to the regenerator inlet; the second segment is the regenerative deceleration segment, from the regenerator inlet to the middle of the checker; the third segment is the regenerative acceleration segment, from the middle of the checker to the regenerator outlet; the fourth segment is the branch pipe transport segment, from the regenerator outlet to the collector inlet; the fifth segment is the collector processing segment, from the collector inlet to the collector outlet; the sixth segment is the main pipe stabilization segment, from the collector outlet to the middle of the main pipe; and the seventh segment is the tuyere impact segment, from the middle of the main pipe to the blast furnace tuyere.

[0095] The Mars motion characteristics, temperature and shape characteristics of each segment are obtained, the motion characteristics including the Mars motion speed vector and acceleration vector, which can be obtained by a laser Doppler velocimeter; the temperature and shape characteristics including the Mars temperature and shape factor, the Mars temperature being obtained by a high-speed polarized infrared camera and a thermocouple.

[0096] Three levels of early warning are set for each segment, including:

[0097] The comprehensive risk index of the corresponding segment is calculated using the Mars speed and the average Mars temperature of each segment ; wherein, T1, V1, R1 and F1 respectively represent the temperature weight, speed weight, static risk weight and exclusive risk factor of the first segment; T2, V2, R2 and F2 respectively represent the temperature weight, speed weight, static risk weight and exclusive risk factor of the second segment; T3, V3, R3 and F3 respectively represent the temperature weight, speed weight, static risk weight and exclusive risk factor of the third segment; T4, V4, T0, ΔT, V5 and ΔV respectively represent the average Mars temperature, reference temperature, maximum allowed temperature deviation, Mars speed, reference speed and maximum allowed speed deviation of the fourth segment;

[0098] The early warning level is determined according to the region where the comprehensive risk index is located, including:

[0099] When the comprehensive risk index is in the first region, it is a first-level early warning; When the comprehensive risk index is in the second region, it is a second-level early warning;

[0100] When the comprehensive risk index is in the third region, it is a third-level early warning.

[0101] When the comprehensive risk index is in the fourth region, it is a fourth-level early warning.

[0102] Wherein, the edge computing is used to locate the abnormality at different positions on the Mars flow path in real time and trigger the warning of the corresponding level, including the following steps:

[0103] A Mars motion trajectory model is constructed , wherein, T1, V1, R1 and F1 respectively represent the temperature weight, speed weight, static risk weight and exclusive risk factor of the first segment; ​​a position vector, a velocity vector, an acceleration vector, a time step, a Gaussian noise term, a gas density, a Mars particle density, a Mars particle diameter, a drag coefficient, a flow velocity vector, and a gravitational acceleration vector of the Mars at the moment; whether the Mars will collide with the pipe wall or the inner wall of the equipment can be identified through the motion vector of the Mars. Collision of the Mars with the pipe wall indicates that there are Mars in the pipeline, and the collision of the Mars causes local temperature anomaly of the pipeline, resulting in damage to the pipeline.

[0104] a Mars temperature decay prediction model wherein, represents a regression coefficient, represents a Mars average temperature, an ambient temperature, and a gas constant at the moment, represents an edge computing LSTM model; represents a standard activation energy;

[0105] According to the Mars trajectory prediction model and the Mars temperature decay prediction model, the Mars is predicted at each segmented velocity vector and temperature, and the predicted temperature value and the modulus of the velocity vector are taken as input variables and substituted into , and an integrated risk prediction value of each segment is output; according to the size of the integrated risk prediction value, a corresponding level of early warning is output.

[0106] In this embodiment, the specific configuration of the edge computing resource is that an edge computing unit ECU is deployed at each segmented node (combustion chamber outlet, regenerative chamber inlet, Mars catcher, etc.). The hardware configuration of each ECU can be: a multi-core processor, a special FPGA (for accelerating algorithms), a sensor, and a local storage module.

[0107] Step 3, obtaining the early warning position and level, identifying the motion characteristics and temperature characteristics of the Mars to distinguish the composition of the Mars, and diagnosing the fault type of the hot blast furnace according to the composition of the Mars, and taking corresponding response measures, including the following steps:

[0108] obtaining the early warning level of the corresponding segment, if it is a three-level early warning, then obtaining the real-time data stream of the corresponding segment extracting the inertia characteristic index feature , the temperature decay factor , and the radiation spectrum entropy to constitute an input feature vector;

[0109] inputting the input feature vector into a pre-trained classification decision tree model to output the type of Mars particles; the type of Mars particles includes refractory brick particles and unburned fuel particles;

[0110] According to the output type of the Mars particles, re-combustion feature detection is performed, including the following steps:

[0111] acquiring the temperature of the spark particles, the oxygen concentration, the activation energy of the particles and the time of the spark particles flowing through the section in the current section;

[0112] calculating the rekindling probability of the spark particles ; wherein, represents the ignition temperature of the particles and the oxygen concentration, represents the time of the spark particles flowing through the section, respectively represent the temperature change weight coefficient, the environment weight coefficient and the time weight coefficient;

[0113] If , it means that the particles will not rekindle;

[0114] If , it means that the particles will rekindle;

[0115] If , it means that the particles have the possibility of rekindling;

[0116] In combination with the rekindling probability, the type of spark particles is determined, and a hierarchical response is made according to the fault type and the section where it is located, including the following steps:

[0117] If and and , it is judged that the spark particles in the current section are refractory brick particles, and the fault type is refractory brick fault; the response measure taken is to reduce the furnace temperature, and to overhaul the lining of the current section pipeline or the refractory layer in the hot blast stove;

[0118] If and , it is judged that the spark particles in the current section are unburned fuel particles, and the fault type is insufficient combustion; the response measure taken is to adjust the air-fuel ratio or clean the burner nozzle;

[0119] If and or or , it is judged that the spark particles in the current section are a mixture of fuel particles and refractory brick particles, and the fault type is refractory brick fault and combustion fault; then the above two disposal measures are adopted at the same time.

[0120] Example two:

[0121] In reality, in order to reduce sparks, the hot blast stove system is usually provided with a spark catcher, which uses centrifugal force to make sparks collide with the inner wall and then settle down through rotating airflow.

[0122] As a key device in the Mars movement path (segment node), it is necessary to improve the detection accuracy of the Mars movement state and temperature state under rotating airflow to accurately predict the Mars temperature and movement state at this location. To this end, the following technical solutions are proposed:

[0123] By constructing a rotating flow field model, the accuracy of Mars trajectory prediction and temperature measurement under rotating airflow is improved, including:

[0124] Constructing a three-dimensional vortex field analytical model ; wherein, represents the flow velocity vector, represents the air pressure, represents the kinematic viscosity, represents the rotational flow angular velocity vector, represents the Coriolis force term;

[0125] Flow velocity vector ; represents the Mars space position coordinates, represents the POD modal function, represents the number of POD modal functions; time coefficient Obtained by inverting the data of the pipe wall surface pressure sensor;

[0126] Optimize the acceleration vector in the Mars movement trajectory model, add a virtual mass force term: ; wherein, represents the Mars particle velocity vector, represents the particle density; represents the fluid material derivative; ;

[0127] The physical meaning of the virtual mass force is the additional force required to accelerate the fluid, which cannot be ignored when is greater than 0.1;

[0128] Update the Mars movement trajectory model by extended Kalman filtering to obtain the accurate position of Mars;

[0129] Construct a radiation transfer correction model to correct the temperature measurement error caused by the fly ash in the flue gas affecting the radiation coefficient; including the following steps:

[0130] Mars true temperature , wherein, represents the measured temperature of the infrared temperature measuring instrument or the predicted temperature of the Mars temperature decay prediction model, represents the fly ash absorption coefficient; represents the fly ash concentration; represents the radiation propagation path, represents the path integral unit;

[0131] A dynamic response compensation model is constructed to compensate for the delay in dynamic response caused by thermal inertia of the thermocouple, resulting in a delay in temperature measurement; comprising:

[0132] Thermocouple response model ;

[0133] Thermal inertia of thermocouple causes measurement lag ; wherein, represents the real gas temperature, the thermocouple strategy temperature, and the thermal response time at the moment;

[0134] Then, the final temperature after compensation is ;

[0135] Based on the final temperature after compensation, the comprehensive risk index is recalculated, and according to the size of the recalculated risk index, different levels of early warning are output.

[0136] Embodiment three:

[0137] After segmenting the motion path of Mars, abnormal fluctuations in upstream segment parameters may cause false alarms in downstream segments. In order to reduce false alarms and ensure the robustness of early warning, the following technical solutions are proposed:

[0138] Before outputting the corresponding level of early warning according to the size of the comprehensive risk prediction value, the processing effect of the upstream segment on Mars is evaluated, including the following steps:

[0139] Obtain the number of Mars at the inlet and outlet of the segment , calculate the Mars capture efficiency ; in this embodiment, the number of Mars can be obtained by a laser particle counter.

[0140] Obtain the temperature of the Mars at the inlet and outlet of the segment , calculate the Mars cooling efficiency ; in this embodiment, the temperature information of the Mars can be obtained by deploying an infrared thermal imager array.

[0141] Obtain the velocity vector of the Mars at the inlet and outlet of the segment , calculate the Mars speed reduction efficiency ; in this embodiment, the velocity vector information of the Mars can be obtained by a cross-correlation flowmeter.

[0142] Obtain the flow rate of the Mars at the inlet and outlet of the segment , calculate the Mars residual flux ; in this embodiment, the flow rate of the Mars can be obtained by a weighing-type dust instrument.

[0143] Construct a qualification judgment function:

[0144] ; wherein, represents a Heaviside step function, ; respectively represent a Mars capture rate threshold value, a temperature reduction efficiency threshold value, a speed reduction efficiency threshold value, and a residual flux threshold value;

[0145] If the segmented qualified judgment function value is greater than the preset qualified threshold value, it is judged that the segmented Mars treatment effect is qualified; otherwise, it is unqualified.

[0146] Then, it is judged whether the upstream segmented parameter anomaly will cause false alarm of the downstream segment and the influence of quantifying the upstream segmented abnormal parameter change on the downstream monitoring.

[0147] The specific steps are as follows:

[0148] The upstream and downstream influence analysis model is constructed, including the following steps:

[0149] The transfer equation of temperature and speed is constructed ; wherein, The real temperature passing through the Mars is calculated at this time;

[0150] The constraint equation of temperature and speed is constructed ; wherein, the temperature safety margin , the speed safety margin ; respectively represent a downstream temperature alarm threshold value and a downstream speed alarm threshold value; represent a temperature safety coefficient and a speed safety coefficient; represent the Mars speed under the rated operating condition of the downstream segment; the safety margin is self-adaptively adjusted with the operating condition to adapt to the requirements of different segmented temperature changes and speed changes.

[0151] Coupling the transfer matrix in , respectively represent a temperature self-transfer coefficient, a temperature-to-speed influence coefficient, a speed-to-temperature influence coefficient, and a speed self-transfer coefficient; the non-diagonal term reflects the temperature-speed cross influence, and the environmental temperature coefficient ensures the model regression.

[0152] The Mars temperature safety range in the segment is , wherein, ;

[0153] The Mars speed safety range in the segment is , wherein, ;

[0154] If the change range of the upstream abnormal parameter is within the temperature safety range and the speed safety range, it is judged that the upstream parameter anomaly will not cause downstream false alarm;

[0155] Quantifying the influence of upstream segment abnormal parameter changes on downstream monitoring, including:

[0156] Setting a temperature influence index , a speed influence index ;

[0157] Obtaining a comprehensive influence degree ; wherein, respectively represent the temperature influence weight and the speed influence weight, representing the average temperature of the downstream segment under the rated operating condition of the downstream segment;

[0158] If , the influence degree on the downstream is determined to be level one;

[0159] If , the influence degree on the downstream is determined to be level two;

[0160] If , the influence degree on the downstream is determined to be level three;

[0161] If , the influence degree on the downstream is determined to be level four.

[0162] If the influence degree is level one, the existing data acquisition state is maintained; if the influence degree is level two, the monitoring frequency is increased and the data acquisition frequency is increased; if the influence degree is level three, an alarm information is sent out to check whether there is a fault in the upstream segment; and if the influence degree is level four, an alarm is triggered and the upstream segment and the downstream segment at the position are isolated.

[0163] The application also provides a hot blast stove star edge calculation hierarchical response cloud platform early warning system, comprising a plurality of edge calculation units and a communication module connected with the edge calculation units, and the system is used for executing the hot blast stove star edge calculation hierarchical response method.

[0164] The application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the hot blast stove star edge calculation hierarchical response method.

[0165] The processes described above with reference to the flowcharts can be implemented as computer software programs in accordance with embodiments of the present disclosure. Embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication section, and / or installed from a detachable medium. When the computer program is executed by a central processing unit (CPU), the above-described functions defined in the methods of the present application are performed. It should be noted that the computer readable medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus or device. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave, in which the computer readable program code is carried. Such a propagated data signal can take many forms, including but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium that can send, propagate or transfer a program for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to, wireless, wire line, optical fiber, RF, etc., or any suitable combination of the above.

[0166] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0167] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are merely examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functions and structural principles of the present invention have been shown and explained in the embodiments. Without departing from the principles described, the implementation of the present invention may have any changes or modifications.

Claims

1. A hierarchical response calculation method for the Martian edge of a hot blast stove, characterized in that, The method includes: Retrieve Mars's trajectory and the information of the equipment it passes through from the database; A segmented and hierarchical early warning strategy is constructed, which uses edge computing to locate anomalies at different locations along the Martian flow path in real time and triggers warnings of corresponding levels. Specifically, this includes: Constructing a Mars trajectory model ,in, They represent The position vector, velocity vector, acceleration vector, time step, Gaussian noise term, gas density, Martian particle density, Martian particle diameter, drag coefficient, flow velocity vector, and gravitational acceleration vector of Mars at any given moment; Mars temperature decay prediction model ,in, Represents the regression coefficient. express The average temperature, ambient temperature, and gas constant of Mars at any given time. This represents an edge computing LSTM model; Indicates the standard activation energy; Based on the Mars trajectory prediction model and the Mars temperature decay prediction model, the velocity vector and temperature of Mars in each segment are predicted. The predicted temperature value and the magnitude of the velocity vector are used as input variables and substituted into... Output the comprehensive risk prediction value for each segment; Based on the magnitude of the comprehensive risk forecast, an early warning of the corresponding level is issued; The system obtains the location and level of the early warning, identifies the motion and temperature characteristics of Mars to distinguish its composition, diagnoses the fault type of the hot air furnace based on the Martian composition, and takes corresponding response measures.

2. The method for calculating the hierarchical response of a hot blast stove at the edge of Mars, as described in claim 1, is characterized in that... The construction of the segmented and hierarchical early warning strategy includes: The Martian flow path is segmented based on key equipment along the Martian flow path, the inflection points of Martian temperature and Martian velocity, and the potential hazards on Mars. The motion, temperature, and shape features of Mars for each segment are obtained. The motion features include the Martian motion velocity vector and acceleration vector; the temperature and shape features include the Martian temperature and shape factor. Each segment has three warning levels, including: The comprehensive risk index for each segment is calculated using the Martian velocity and average Martian temperature. ;in, They represent the first The segment's temperature weight, speed weight, static risk weight, and specific risk factors; They represent the first Average temperature of Mars, reference temperature, maximum permissible temperature deviation, Mars velocity, reference velocity, and maximum permissible velocity deviation; The warning level is determined based on the region where the comprehensive risk index is located, including: when It was at the level of Level 1 warning; when The alert level is currently Level II. when The alert level is currently at Level 3.

3. The method for calculating the hierarchical response of a hot blast stove at the edge of Mars, as described in claim 2, is characterized in that... The method of using edge computing to locate anomalies at different locations along the Martian flow path in real time and trigger warnings of corresponding levels also includes: Improving the accuracy of Mars trajectory prediction and temperature measurement under rotating airflow by constructing a rotating flow field model, including: Constructing a three-dimensional vortex field analytical model ;in, Represents the velocity vector. Indicates air pressure. Indicates kinematic viscosity. Represents the angular velocity vector of the swirling stream; Flow velocity vector ; Represents the spatial coordinates of Mars. Represents the POD mode function. Indicates the number of POD modes; time coefficient This was derived by inverting data from pressure sensors on the pipe wall. Optimize the acceleration vector in the Mars motion trajectory model by adding a virtual mass force term: ;in, This represents the velocity vector of the Martian particles. Indicates particle density; Represents the mass derivative of a fluid; ; The updated Mars trajectory model is solved by extended Kalman filtering to obtain the accurate location of Mars. A radiative transfer correction model is constructed to correct temperature measurement errors caused by the coefficient of radiation from fly ash in flue gas; including: The true temperature of Mars ,in, This indicates the temperature measured by the infrared thermometer or the predicted temperature from the Mars temperature decay prediction model. Indicates the fly ash absorption coefficient; Indicates fly ash concentration; Indicates the radiation propagation path, Represents the path integral unit; A dynamic response compensation model is constructed to compensate for the dynamic response delay caused by the thermal inertia of thermocouples, which results in a delay in temperature measurement; this includes: Thermocouple response model Thermocouple thermal inertia causes measurement lag ;in, express Real-time gas temperature, thermocouple strategy temperature, and thermal response time; Therefore, the final temperature after compensation is The comprehensive risk index is recalculated based on the supplemented final temperature, and different levels of warnings are output according to the magnitude of the recalculated risk index.

4. The method for calculating the hierarchical response of a hot blast stove at the edge of Mars according to claim 3, characterized in that, Before issuing an early warning of the appropriate level based on the magnitude of the comprehensive risk forecast, the following steps are also included: The assessment of the upstream segment's effect on Mars processing includes: Obtain the number of segmented entry and exit points on Mars. Calculate Mars capture efficiency Obtain the temperatures of the segmented entry and exit points of Mars. Calculate the cooling efficiency of Mars Obtain the velocity vectors of the segmented entry and exit points of Mars. Calculate the deceleration efficiency of Mars Obtain segmented inlet and outlet Mars traffic Calculate the residual flux on Mars Construct a pass / fail judgment function: ;in, This represents the Heaviside step function. These represent the Mars capture rate threshold, cooling efficiency threshold, deceleration efficiency threshold, and residual flux threshold, respectively. If the pass / fail value of a segment is greater than the preset pass / fail threshold, the segmented spark processing effect is considered passable; otherwise, it is considered failable.

5. The method for calculating the hierarchical response of a hot blast stove at the edge of a Martian surface according to claim 4, characterized in that, Before issuing an early warning of the appropriate level based on the magnitude of the comprehensive risk forecast, the following steps are also included: Determine whether abnormal upstream segment parameters will cause false alarms in downstream segments; Quantify the impact of abnormal parameter changes in upstream segments on downstream monitoring.

6. The method for calculating the hierarchical response of a hot blast stove at the edge of Mars, as described in claim 5, is characterized in that... The determination of whether abnormal upstream segment parameters will cause false alarms in downstream segments includes: Construct an upstream and downstream impact analysis model, including: Constructing the transfer equations for temperature and velocity in, At this point, calculations are performed based on the actual temperature of Mars; Constructing constraint equations for temperature and velocity Among them, temperature safety margin Speed ​​safety margin These represent the downstream temperature alarm threshold and the downstream speed alarm threshold, respectively. This indicates the temperature safety factor and the speed safety factor; This indicates the Martian velocity under rated operating conditions in the downstream segment; Coupled transfer matrix In These represent the temperature self-transfer coefficient, the temperature-velocity influence coefficient, the velocity-temperature influence coefficient, and the velocity self-transfer coefficient, respectively. The safe temperature range for Mars within the segment is: ,in, The safe range for Mars velocity within the segment is: ,in, If the variation range of the upstream abnormal parameters is within the safe range of temperature and speed, it can be determined that the abnormality of the upstream parameters will not cause false alarms downstream. Quantifying the impact of upstream segmented abnormal parameter changes on downstream monitoring, including: Set the temperature effect index Speed ​​Influence Index Obtaining overall influence in, These represent the weights of temperature and speed, respectively. This indicates the average temperature of the sparks under rated operating conditions in the downstream section; if The impact on downstream industries is then classified as Level 1. if The impact on downstream industries is then classified as Level 2. if The impact on downstream industries is then classified as Level 3. if The impact on downstream areas is then classified as level four.

7. The method for calculating the hierarchical response of a hot blast stove at the edge of Mars according to claim 6, characterized in that, The process involves acquiring the location and level of the early warning, identifying the motion and temperature characteristics of Mars to distinguish its composition, diagnosing the fault type of the hot blast stove based on its composition, and taking corresponding response measures, including: Obtain the warning level for the corresponding segment. If it is a level three warning, obtain the real-time data stream for the corresponding segment. Extracting inertial feature index features Temperature decay factor and spectral entropy of radiation Construct the input feature vector; The input feature vector is fed into a pre-trained classification decision tree model, which outputs the type of Martian particles; the types of Martian particles include refractory brick particles and unburned fuel particles. Based on the type of Martian particles output, reignition feature detection includes: Obtain the temperature, oxygen concentration, particle activation energy, and time it takes for Martian particles to flow through the segment within the current segment; Calculate the probability of Martian particles reigniting in, This indicates the particle ignition temperature and oxygen concentration. This indicates the time it takes for Martian particles to travel through a segment. These represent the weighting coefficients for temperature change, environment, and time, respectively. if This indicates that the particles will not reignite; if This indicates that the particles may reignite; if This indicates that the particles may reignite; Based on the re-ignition probability, the type of Martian particles is determined, namely: if and and When the sparks in the current segment are determined to be refractory brick particles, the fault type is refractory brick fault. if and When the sparks in the current segment are determined to be unburned fuel particles, the fault type is incomplete combustion. if and or or If the sparks in the current segment are determined to be a mixture of fuel particles and refractory brick particles, the fault type is refractory brick fault and combustion fault. Based on the fault type and the segment in which it occurs, a graded response is implemented.

8. A Mars edge computing hierarchical response cloud platform early warning system for hot blast stoves, comprising multiple edge computing units and communication modules connected to the edge computing units, characterized in that: The system is used to execute the hot blast stove Martian edge calculation hierarchical response method according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the hot blast stove Martian edge calculation hierarchical response method according to any one of claims 1-7.

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