Steel slag pressure hot stuffiness rolling cooling water abnormity alarm system and method

Abstract

The invention relates to the technical field of cooling water abnormity monitoring, in particular to a steel slag pressure hot stuffy rolling cooling water abnormity alarm system and method.Roll gap cooling water flow, injection temperature, hot stuffy tank pressure and bearing vibration data are collected, a dynamic mapping relation between position coordinates of a spraying opening and a water inlet valve is established, temperature and pressure time sequence offset is calculated, and the temperature and pressure time sequence offset is calculated; the temperature judgment boundary is corrected by combining the pressure bearing limit value of the sealing ring and the real-time flow, and an abnormal alarm is triggered according to the temperature over-limit frequency in the continuous time period. A multi-source analysis framework is constructed by integrating temperature, flow, pressure and vibration parameters, single-point monitoring limitation is eliminated, nonlinear influence of the flow on tank pressure is quantified by adopting a dynamic weight model, a self-adaptive temperature threshold value is generated in combination with a sealing pressure bearing limit, dynamic coupling of an alarm mechanism is realized, an abnormal scene is positioned based on time sequence analysis and coordinate mapping, and the accuracy of monitoring is improved. The sealing hidden danger is pre-judged through the thermal unbalance coefficient, and the pressure rate deviation is intercepted in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of cooling water anomaly monitoring, and in particular to a cooling water anomaly alarm system and method for a steel slag press with hot rolling. Background Art

[0002] The field of cooling water anomaly monitoring technology encompasses real-time monitoring and anomaly diagnosis of industrial cooling system operations. Core content revolves around the acquisition of cooling medium parameters, data transmission, and anomaly detection logic. This systematic approach involves the deployment of temperature sensor networks, flow fluctuation detection devices, pressure change tracking equipment, and the construction of alarm triggering mechanisms. It focuses on addressing the engineering and technical challenges of early warning of cooling system failure risks in high-temperature operations such as metallurgy and chemical engineering. Its technical system encompasses a complete link architecture spanning the physical quantity perception layer, data processing layer, and decision-making execution layer.

[0003] The slag hot roller press cooling water anomaly alarm system is a monitoring device designed for the cooling water circuit of the slag roller press. It covers three technical aspects within the roller press's cooling water circuit: vibration amplitude detection, water temperature gradient monitoring, and identification of sudden changes in water flow rate. Parameters are collected through vibration sensors installed on the roller support, distributed temperature sensors embedded in the cooling pipe walls, and a turbine flowmeter at the circulating pump outlet. Data is then evaluated using a programmable logic controller's built-in threshold comparison algorithm. Finally, an audible and visual alarm system and the central control room's human-machine interface form an output channel for abnormal conditions.

[0004] Existing technologies use isolated parameter threshold alarms, lack a dynamic correlation model between parameters, and have a high misjudgment rate. Flow anomalies cannot be correlated with pressure changes to verify the cause, vibration monitoring does not cover the resonance effects of bearings and pipelines, and mechanical vibration resistance anomalies are missed. Fixed thresholds do not combine the seal pressure resistance with the pressure accumulation rate, and flow rate drops that cause seal overpressure are not promptly warned. There is a lack of topological correlation between the spray port and the water inlet valve, making it impossible to accurately trace the fault section. Single-point threshold comparison ignores the continuity of the time series, falsely reporting instantaneous fluctuations and missing gradual temperature rises. Alarm information lacks spatial coordinates and conduction paths, extending troubleshooting time. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a cooling water abnormality alarm system and method for hot rolling of steel slag.

[0006] In order to achieve the above-mentioned object, the present invention adopts the following technical solution: a steel slag hot roller press cooling water abnormality alarm system, the system comprising:

[0007] The roll nip parameter monitoring module collects the flow rate and injection temperature of the roll gap cooling water branch, obtains the cooling water pressure value in the hot stuffy tank, monitors the vibration amplitude of the roll bearing, aligns each parameter type by time stamp, and generates a four-dimensional roll parameter set;

[0008] The hot stuffy tank topology association module associates the coordinates of the hot stuffy tank water inlet valve with the position of the roller spray port based on the roller pressing four-dimensional parameter set, establishes a real-time mapping relationship between the roller gap flow, the hot stuffy tank pressure and the bearing vibration, and generates a hot stuffy tank topology association diagram;

[0009] The spray failure reasoning module integrates the four-dimensional roll pressure parameter set and the hot stuffy tank topology association diagram, calculates the deviation between the roll gap spray temperature and the hot stuffy tank pressure, and generates the roll gap hot stuffy tank thermal imbalance coefficient;

[0010] The sealing pressure threshold module matches the thermal imbalance coefficient of the roll gap hot stuffy tank with the pressure limit value of the hot stuffy tank seal ring, dynamically modifies the temperature alarm threshold according to the current roll gap cooling water branch flow value, and generates a roll nip area temperature safety threshold;

[0011] The roller pressing abnormality alarm module calls the real-time roller gap cooling water injection temperature value in the roller pressing four-dimensional parameter set, performs time series continuity judgment with the roller pressing area temperature safety threshold, and generates a slag roller pressing cooling failure alarm instruction.

[0012] As a further solution of the present invention, the four-dimensional parameter set of rolling includes a roll gap flow timing sequence, a spray temperature timing sequence, a tank pressure timing sequence, and a bearing vibration timing sequence. The hot stuffy tank topology association diagram is specifically a valve port spray coordinate mapping relationship, a flow pressure dynamic association matrix, and a vibration pressure conduction topology path. The thermal imbalance coefficient of the roll gap hot stuffy tank includes a temperature-pressure dynamic deviation rate, a heat conduction gradient difference, and a heat exchange attenuation factor. The temperature safety threshold of the roll pressure zone is specifically a dynamic threshold range, a pressure-flow coupling coefficient, and a sealing ring deformation critical value. The slag roll pressing cooling failure alarm instruction includes a temperature over-limit interval mark, a cooling interruption timing positioning, and a spray failure trigger signal type.

[0013] As a further solution of the present invention, the roller nip parameter monitoring module includes:

[0014] The data acquisition submodule synchronously collects the cooling water injection temperature value from the temperature sensor, the branch flow value from the electromagnetic flowmeter, the tank water pressure value from the pressure sensor, and the bearing vibration amplitude value from the vibration sensor. It stores the four types of parameters according to independent time stamps and generates an original parameter set containing temperature, flow, pressure, and vibration.

[0015] The timing alignment submodule calls the parameter timestamps in the original parameter set, aligns the sampling points of the temperature, flow, and pressure values according to a unified time reference, constrains the time difference between the vibration value and the temperature value to a preset range, extracts the four types of parameters within the synchronization time window, and generates a synchronization parameter sequence with a time stamp;

[0016] The parameter fusion submodule interpolates the temperature, flow, and pressure values in the synchronized parameter sequence to fill in the missing data, smoothes and denoises the vibration values, aligns the four types of parameters into vectors of equal length according to timestamps, integrates them into multidimensional data units, and generates a four-dimensional roller pressing parameter set with time stamps.

[0017] As a further solution of the present invention, the hot tank topology association module includes:

[0018] The coordinate association submodule calls the branch flow value in the roller pressing four-dimensional parameter set, extracts the roller pressing roller spray port position coordinates and the hot stuffy tank water inlet valve coordinates, matches the spatial distribution relationship of the two coordinates, establishes the pipeline connection mapping between the spray port and the water inlet valve, and generates a coordinate mapping table containing the position correspondence relationship;

[0019] The weight calculation submodule associates the time series data of the branch flow value and the hot and stuffy tank pressure value based on the pipeline connection relationship in the coordinate mapping table, calculates the matching degree of the fluctuation trend of the flow value and the pressure value, generates a proportional factor based on the pipeline length and cross-sectional parameters, quantifies the influence weight of the flow on the pressure, and generates a linear correlation weight coefficient;

[0020] The topology generation submodule calls the linear correlation weight coefficient and the bearing vibration value in the rolling four-dimensional parameter set, superimposes the vibration amplitude and weight coefficient according to the pipeline node, constructs a three-dimensional relationship matrix of flow-pressure-vibration, arranges the matrix units according to the loop path connection rules, and generates a hot and stuffy tank topology association diagram including the node association strength.

[0021] As a further solution of the present invention, the spray failure reasoning module includes:

[0022] The pressure change quantification submodule calls the real-time data of the roller gap cooling water injection temperature in the roller pressing four-dimensional parameter set, obtains the flow and pressure association weights in the hot tank topology association diagram, calculates the pressure change gradient corresponding to the unit flow increment, and generates the unit pressure change of the flow pressure change;

[0023] The deviation amplitude calculation submodule extracts the current flow value and the actual hot and stuffy tank pressure value based on the unit pressure change, calculates the theoretical matching curve of the injection temperature and pressure value, compares the absolute value of the difference between the measured temperature and the theoretical curve, and generates a temperature and pressure deviation degree that reflects the degree of temperature and pressure deviation;

[0024] The thermal imbalance derivation submodule calls the temperature and pressure deviation and the roll gap cooling water flow value, accumulates the deviation and flow value in a time series, superimposes the pressure accumulation effect caused by insufficient flow, calculates the total pressure imbalance per unit time, and generates the roll gap hot stuffy tank thermal imbalance coefficient that quantifies the degree of cooling abnormality.

[0025] As a further solution of the present invention, the sealing pressure threshold module includes:

[0026] The reverse correlation quantification submodule calls the thermal imbalance coefficient of the roll gap hot stuffy tank, extracts the time series data of the hot stuffy tank pressure accumulation rate and the cooling water flow rate, calculates the negative correlation slope of the pressure rate with the flow rate, and generates a reverse correlation factor describing the flow rate suppressing the pressure growth rate;

[0027] The pressure limit matching submodule, based on the reverse correlation factor, calls the maximum pressure strength data of the sealing ring, matches the difference between the current pressure accumulation rate and the pressure limit value of the sealing ring, calculates the risk probability of the pressure growth exceeding the limit per unit time, and generates a pressure limit threshold reflecting the risk of seal failure;

[0028] The threshold correction submodule calls the pressure limit threshold and the flow value of the roll gap cooling water branch, converts the flow value into a pressure suppression coefficient according to the inverse correlation factor, superimposes the correction weight of the current thermal imbalance coefficient on the pressure accumulation, dynamically adjusts the temperature alarm boundary value, and generates a roll nip area temperature safety threshold that adapts to the working conditions in real time.

[0029] As a further solution of the present invention, the roller pressure abnormality alarm module includes:

[0030] The threshold comparison submodule calls the real-time cooling water temperature value of the roller pressing four-dimensional parameter set to obtain the roller pressing zone temperature safety threshold, compares the temperature sampling data with the threshold range frame by frame, counts the number of consecutive time windows in which the temperature exceeds the threshold, and generates an over-limit status indicator reflecting the temperature over-limit status;

[0031] The abnormality positioning submodule, based on the excessive state identifier, calls the data on the excessive pressure of the hot and stuffy tank and the location parameters of the roller gap spray branch, calculates the linear correlation coefficient between the duration of the temperature excess and the pressure increase, determines the probability weight of the abnormal source being the spray branch or the cooling pipeline, and generates a continuous excessive coefficient including the abnormal area mark;

[0032] The alarm generation submodule calls the continuous exceeding coefficient, extracts the spray branch position code and the exceeding pressure of the hot stuffy tank, matches the abnormal area mark and the pressure increase according to the preset alarm rules, constructs a mapping relationship between the abnormal type and the level, and generates a slag roller cooling failure alarm instruction including the position code and the pressure amplitude.

[0033] A method for alarming abnormal cooling water of hot steel slag roller pressing is provided. The method is based on the above-mentioned abnormal cooling water alarm system for hot steel slag roller pressing and includes the following steps:

[0034] S1: Monitor the flow rate and injection temperature of the cooling water branch in the roll gap of the roll press area, collect the cooling water pressure value in the hot stuffy tank and the vibration amplitude value of the roll press bearing, align each type of parameter by time stamp and integrate them into a unified time series to generate a four-dimensional roll press parameter set;

[0035] S2: Based on the four-dimensional roller pressing parameter set, the roller spray port position coordinates and the hot stuffy tank water inlet valve coordinates are extracted, a dynamic mapping relationship between the roller gap flow, hot stuffy tank pressure and bearing vibration amplitude is established, and a hot stuffy tank topology association diagram is generated;

[0036] S3: calling the roll gap injection temperature value and the hot stuffy tank pressure value in the roll pressing four-dimensional parameter set, calculating the standard deviation and mean offset of the two in the time series dimension, and generating the roll gap hot stuffy tank thermal imbalance coefficient;

[0037] S4: Based on the thermal imbalance coefficient of the roll gap hot stuffy tank and the preset pressure limit value of the hot stuffy tank sealing ring, combined with the current flow value of the roll gap cooling water branch, the temperature judgment boundary is dynamically adjusted using a linear interpolation method to generate a temperature safety threshold of the roll nip area;

[0038] S5: Based on the real-time roll gap cooling water injection temperature value in the roll pressing four-dimensional parameter set and the roll pressing zone temperature safety threshold, the over-limit frequency statistics within the continuous time window are performed. When the alarm condition is triggered, a slag roll pressing cooling failure alarm instruction is generated.

[0039] Compared with the prior art, the advantages and positive effects of the present invention are:

[0040] In the present invention, by integrating four types of parameters, namely roller gap cooling water temperature, flow rate, pressure and vibration, a multi-source collaborative analysis framework is constructed to eliminate the isolation of single-point monitoring. Through dynamic weight calculation combined with vibration correction coefficient, a conduction model is established to quantify the nonlinear effect of flow fluctuations on tank pressure. An adaptive temperature threshold is generated in combination with the pressure resistance of the sealing ring, and the alarm mechanism is dynamically coupled with the pressure limit of the equipment. Time series analysis is combined with coordinate mapping to accurately locate scenarios such as blockage or inlet failure. The thermal imbalance coefficient is introduced to predict the hidden dangers of sealing overpressure, and the pressure rate and sealing threshold are compared in real time to intercept progressive risks. Topological modeling of the spray port and the water inlet valve realizes the tracing of abnormal sections and shortens the troubleshooting cycle. Multi-dimensional parameter cross-validation and dynamic weight correction improve the diagnostic accuracy, avoid misjudgment or omission of fixed thresholds, and realize the upgrade from passive alarm to active protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a system flow chart of the present invention;

[0042] Figure 2 This is a flow chart of obtaining the roll nip parameter monitoring module of the present invention;

[0043] Figure 3 This is a flowchart of obtaining the hot and stuffy tank topology association module of the present invention;

[0044] Figure 4 This is a flow chart for obtaining the spray failure reasoning module of the present invention;

[0045] Figure 5 This is a flow chart for obtaining the sealing pressure threshold module of the present invention;

[0046] Figure 6 This is an acquisition flow chart of the roller pressure abnormality alarm module of the present invention. DETAILED DESCRIPTION

[0047] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0048] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0049] In the embodiments of the present invention, the terms "image" and "picture" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same. The terms "of," "corresponding," and "corresponding" may be used interchangeably. It should be noted that, when the distinction between them is not emphasized, their intended meanings are the same.

[0050] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0051] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0052] See also Figure 1 The present invention provides a technical solution: a steel slag hot roller pressing cooling water abnormality alarm system, the system includes:

[0053] The roll nip parameter monitoring module uses a temperature sensor to collect the real-time temperature of the cooling water injection in the roll gap, an electromagnetic flowmeter to obtain the flow rate of the cooling water branch in the roll gap, a pressure sensor to monitor the cooling water pressure in the hot stuffy tank, and a vibration sensor to record the vibration amplitude of the roll bearing. Each parameter type is aligned by time stamp to generate a four-dimensional roll nip parameter set including temperature, flow, pressure, and vibration.

[0054] The hot stuffy tank topology association module extracts the coordinate data of the roller spray port and the hot stuffy tank water inlet valve based on the roll gap cooling water branch flow value in the four-dimensional roll pressing parameter set, associates the hot stuffy tank water inlet valve coordinates with the roller spray port position, and establishes a real-time mapping relationship between the roll gap flow, hot stuffy tank pressure, and bearing vibration. Through the pipe connection relationship of the hot stuffy tank cooling water circulation path, the linear correlation weight between the roll gap spray flow and the hot stuffy tank pressure is calculated. Combined with the correction coefficient of the bearing vibration amplitude value on the pipeline resonance, it generates a hot stuffy tank topology association diagram reflecting the cooling water circulation path of the slag roller press;

[0055] The spray failure inference module calls the roll gap cooling water spray temperature value in the four-dimensional roll pressing parameter set to obtain real-time data on the cooling water spray temperature at the roll gap. Combined with the roll gap flow rate and the hot stuffy tank pressure association weights in the hot stuffy tank topology association diagram, it extracts the hot stuffy tank pressure change corresponding to each unit increase in the roll gap spray flow rate. The deviation between the roll gap spray temperature and the hot stuffy tank pressure is calculated. The accumulated hot stuffy tank pressure caused by insufficient roll gap cooling water flow is deduced through difference calculation, generating a roll gap hot stuffy tank thermal imbalance coefficient that characterizes the cooling water spray anomaly.

[0056] The sealing pressure threshold module extracts the thermal imbalance coefficient of the roll gap hot stuffy tank, obtains the inverse correlation value between the current hot stuffy tank pressure accumulation rate and the roll gap cooling water flow rate, matches the hot stuffy tank sealing ring pressure limit value in the slag roller pressing process, calls the maximum compressive strength data of the sealing ring in the hot stuffy tank material parameters, and converts the flow value into the suppression coefficient of the hot stuffy tank pressure growth rate based on the current roll gap cooling water branch flow value. It dynamically corrects the temperature alarm threshold and generates a roll pressure zone temperature safety threshold to prevent seal failure.

[0057] The roller pressing abnormality alarm module calls the real-time roller gap cooling water spray temperature value in the roller pressing four-dimensional parameter set, obtains the cooling water temperature sampling data at the current roller gap, compares it frame by frame with the temperature safety threshold of the roller pressing area, and determines whether the temperature value exceeds the threshold continuously through time series analysis. When the temperature value continuously exceeds the threshold, the abnormal position is located as the roller gap spray branch or the hot stuffy tank cooling pipeline, and a slag roller pressing cooling failure alarm instruction is generated, including the roller gap spray failure position and the hot stuffy tank pressure exceeding the standard.

[0058] The four-dimensional parameter set of roller pressing includes the roller gap flow timing sequence, the injection temperature timing sequence, the tank pressure timing sequence, and the bearing vibration timing sequence. The hot stuffy tank topology association diagram specifically includes the valve port spray coordinate mapping relationship, the flow pressure dynamic association matrix, and the vibration pressure conduction topology path. The thermal imbalance coefficient of the roller gap hot stuffy tank includes the temperature and pressure dynamic deviation rate, the heat conduction gradient difference, and the heat exchange attenuation factor. The temperature safety threshold of the roller pressing area is specifically the dynamic threshold range, the pressure-flow coupling coefficient, and the sealing ring deformation critical value. The slag roller pressing cooling failure alarm instruction includes the temperature limit interval mark, the cooling interruption timing positioning, and the spray failure trigger signal type.

[0059] See also Figure 2 , the roller nip parameter monitoring module includes:

[0060] The data acquisition submodule synchronously collects the cooling water injection temperature value from the temperature sensor, the branch flow value from the electromagnetic flowmeter, the tank water pressure value from the pressure sensor, and the bearing vibration amplitude value from the vibration sensor. It stores the four types of parameters according to independent time stamps and generates an original parameter set containing temperature, flow, pressure, and vibration.

[0061] Taking the temperature sensor model PT100 as an example, the Modbus protocol is called to obtain the cooling water injection temperature value, the sampling frequency is set to 100Hz, the branch flow value of the electromagnetic flowmeter model E+H80F is synchronously collected, the RS485 interface is called to read the instantaneous flow data, the water pressure value collection interval of the pressure sensor model MBS3200 is configured to be 10ms, and the 4-20mA signal is transmitted. The sampling period of the vibration sensor model VIB-5 is set to 5ms, and the CAN bus protocol is used to obtain the bearing vibration amplitude peak value. An independent timestamp is generated for each parameter, and the timestamp accuracy reaches microseconds. Second level. For example, the temperature value at timestamp 1640000000.123456 is recorded as 65.3°C, the flow value at timestamp 1640000000.123460 is recorded as 12.7 L / min, the pressure value at timestamp 1640000000.123462 is recorded as 3.2 MPa, and the vibration value at timestamp 1640000000.123458 is recorded as 0.15 mm / s. The four types of parameters are stored in independent data tables in the MySQL database in timestamp order to generate the original parameter set including temperature table, flow table, pressure table, and vibration table.

[0062] The timing alignment submodule calls the parameter timestamps in the original parameter set, aligns the sampling points of temperature, flow, and pressure values according to a unified time base, constrains the time difference between vibration and temperature values to a preset range, extracts the four types of parameters within the synchronization time window, and generates a synchronization parameter sequence with a time stamp;

[0063] Set the unified time base to the server clock, extract the temperature value 65.3℃ corresponding to the temperature parameter timestamp 1640000000.123456, calculate the time difference between the flow parameter timestamp 1640000000.123460 and the temperature base as +4μs, and call the linear interpolation formula At t=1640000000.123456, the flow value of 12.68 L / min is inserted. The pressure parameter timestamp 1640000000.123462 has a time difference of +6 μs from the reference time. The same interpolation method is used to obtain 3.19 MPa. The vibration parameter timestamp 1640000000.123458 has a time difference of -2 μs from the reference time. When the absolute value of the time difference exceeds the preset threshold of 5 μs, cubic spline interpolation is called to reconstruct the vibration data to 0.149 mm / s. Within the time window of 1640000000.123456±10 ms, the four-parameter interpolation results are extracted to generate a synchronous parameter sequence including timestamp, temperature 65.3°C, flow rate 12.68 L / min, pressure 3.19 MPa, and vibration 0.149 mm / s.

[0064] The parameter fusion submodule interpolates the temperature, flow, and pressure values in the synchronized parameter sequence to fill in missing data, smoothes and denoises the vibration values, aligns the four types of parameters into vectors of equal length according to timestamps, integrates them into multidimensional data units, and generates a four-dimensional roller pressure parameter set with time stamps;

[0065] For the missing temperature data points in the synchronization sequence, the two adjacent effective values 67.1℃(t-1) and 67.3℃(t+1) are called for linear interpolation to obtain The average value of the first 3 seconds before the traffic loss point is used Fill in the pressure missing points and use exponential smoothing method to calculate S t =α·3.1+(1-α)·3.0(α=0.8) = 0.8×3.1+0.2×3.0=3.08MPa. The vibration data is filtered by a 5-point moving average. The four parameters are resampled into a 100 Hz equally spaced sequence according to the timestamp. The temperature sequence generates 67.2, 67.3, and 67.4°C vectors; the flow sequence generates 12.5, 12.6, and 12.7 L / min vectors; the pressure sequence generates 3.08, 3.09, and 3.10 MPa vectors; and the vibration sequence generates 0.16, 0.15, and 0.15 mm / s vectors. These are integrated into a multidimensional data unit containing timestamps and four-dimensional parameters to generate a four-dimensional parameter set for roller pressing.

[0066] See also Figure 3 , the hot tank topology association module includes:

[0067] The coordinate association submodule calls the branch flow value in the roller pressing four-dimensional parameter set, extracts the roller pressing roller spray port position coordinates and the hot and stuffy tank water inlet valve coordinates, matches the spatial distribution relationship of the two coordinates, establishes the pipeline connection mapping between the spray port and the water inlet valve, and generates a coordinate mapping table containing the position correspondence;

[0068] The branch flow rate value of 12.7L / min in the roller pressing four-dimensional parameter set is called, the spray port coordinates (x1, y1, z1) and the water inlet valve coordinates (x2, y2, z2) are extracted, and the origin of the three-dimensional coordinate system is set to the geometric center of the hot and stuffy tank (0, 0, 0). The spray port coordinates are calibrated to (1250, 780, 320) ± 0.5mm by the laser surveying instrument, and the water inlet valve coordinates are parsed to (1340, 820, 310) ± 1mm by the CAD drawing. The X-axis difference Δx of the two coordinate points is calculated as 1340-1250 = 90mm, the Y-axis difference Δy = 820-780 = 40mm, and the Z-axis difference Δz = 310-320 = -10mm. The spatial distance formula is used to calculate the difference between the two coordinate points. Determine the distance between the two coordinates. When d < 100 mm and the absolute value of the Z-axis height difference |Δz| ≤ 20 mm, activate the pipeline mapping rule, bind the sprinkler port identifier PID_203 to the water inlet valve identifier VID_7, and record the flow value of 12.7 L / min and the corresponding pressure value of 3.2 MPa in the mapping table. For example, the flow rate at timestamp 1640000000.123456 is 12.68 L / min, and the pressure is 3.19 MPa at the same time base. Generate a coordinate mapping table entry containing the position deviation (Δx, Δy, Δz) and the flow and pressure data pair.

[0069] The weight calculation submodule, based on the pipeline connection relationship in the coordinate mapping table, associates the time series data of branch flow values and hot and stuffy tank pressure values, calculates the matching degree of the fluctuation trend of flow values and pressure values, generates a proportional factor based on the pipeline length and cross-sectional parameters, quantifies the weight of the impact of flow on pressure, and generates a linear correlation weight coefficient;

[0070] Read the flow sequence Q = [12.5, 12.6, 12.7] L / min and pressure sequence P = [3.08, 3.09, 3.10] MPa of PID_203 → VID_7 from the coordinate mapping table and calculate the mean flow rate. Pressure average Calculate the deviation value point by point is [-0.1, 0.0, +0.1], For [-0.01, 0.0, +0.01], calculate the covariance Flow standard deviation Pressure standard deviation Correlation coefficient According to the pipe length L = 96.3mm and the cross-sectional area A = πr 2 =π×(5mm) 2 =78.5mm 2 , calculate the hydraulic radius factor The final weight coefficient w=r×k=0.999×10.86=10.84, generating the linear association weight coefficient of the VID_7 node.

[0071] The topology generation submodule uses the linear correlation weight coefficient and the bearing vibration value in the roller pressing four-dimensional parameter set, superimposes the vibration amplitude and weight coefficient according to the pipeline node, constructs a three-dimensional relationship matrix of flow-pressure-vibration, arranges the matrix units according to the cyclic path connection rules, and generates a hot and stuffy tank topology association diagram including the node association strength;

[0072] Call the weight coefficient 10.84 of the PID_203 node, extract the node vibration data sequence V = [0.17, 0.15, 0.16, 0.14, 0.15] mm / s, and calculate its arithmetic mean Set the vibration influence factor α = 0.8 and calculate the node strength value Construct a three-dimensional matrix M i,j,k , where i = 203 (flow node number), j = 7 (pressure node number), k = 5 (vibration level), when the Euclidean distance d between nodes is ≤ 200 mm and the level difference |k m -k n When |≤2, a bidirectional connection channel is established and the intensity value 8.691 is written into the matrix unit M 203,7,5 , connecting adjacent nodes according to the pipeline direction rule, for example, PID_203→VID_7→NID_5 forms a topological edge with a path length of d=96.3+15=111.3mm, and generates a hot and stuffy tank topological association graph containing node coordinates (1250,780,320), (1340,820,310), association strength 8.691, and level identification 5.

[0073] See also Figure 4 , the sprinkler failure reasoning module includes:

[0074] The pressure change quantification submodule calls the real-time data of the roller gap cooling water injection temperature in the four-dimensional roller pressing parameter set, obtains the flow and pressure association weights in the hot tank topology association diagram, calculates the pressure change gradient corresponding to the unit flow increment, and generates the unit pressure change of the flow-pressure change;

[0075] Call the branch flow sequence numbered PID_203 in the roller pressure four-dimensional parameter set, extract the flow data points [12.5, 12.6, 12.7, 12.6, 12.5] L / min with an interval of 20ms from the timestamp 1640000000.123456 to 1640000000.123476, and simultaneously obtain the weight coefficient 10.84 of the VID_7 node in the hot and stuffy tank topology association diagram. This coefficient is based on the pipe length 96.3mm and the cross-sectional area 78.5mm 2 The calculation shows that the pressure sequence of the corresponding time window is [3.08, 3.09, 3.10, 3.09, 3.08] MPa. Three consecutive data points are selected to calculate the flow increment ΔQ = 12.7-12.5 = 0.2 L / min, the pressure increment ΔP = 3.10-3.08 = 0.02 MPa, and the pressure change gradient When the gradient value is in the preset range [0.05, 0.15], it is judged to be normal. This range is set based on historical data statistics: when the flow rate suddenly changes by more than ±20% of the rated value of 15L / min (i.e. 12-18L / min), the gradient exceeds 0.15, an alarm is triggered. For example, when the flow rate suddenly increases to 18L / min, the measured pressure change gradient is 0.18, which exceeds the threshold and generates an abnormal mark. If the gradient is lower than 0.05 (such as a flow rate of 12L / min corresponds to a pressure increase of only 0.01MPa), it is determined that the spray pipeline is blocked, and the current gradient of 0.1 is written to the log file, generating a unit pressure change of 0.1MPa / (L / min) for the flow-pressure change.

[0076] The deviation amplitude calculation submodule extracts the current flow value and the actual hot tank pressure value based on the unit pressure change, calculates the theoretical matching curve of the injection temperature and pressure value, compares the absolute value of the difference between the measured temperature and the theoretical curve, and generates a temperature and pressure deviation degree that reflects the degree of temperature and pressure deviation;

[0077] Based on the unit pressure change of 0.1MPa / (L / min), call the flow value of 12.7L / min at the current timestamp 1640000000.123466 to calculate the theoretical pressure value P 理论 =12.7×0.1+3.0=4.27MPa, where the baseline pressure of 3.0MPa comes from the equipment rated parameters, and the actual hot tank pressure sensor data is 3.19MPa, and the absolute difference ΔP is calculated. 实际 =|4.27-3.19|=1.08MPa, set the deviation threshold ΔP max =1.2MPa, the threshold is set according to 24% of the maximum tolerance pressure of 5.0MPa of the hot stuffy tank (5.0×24%=1.2), and the normalized deviation is calculated. When D > 0.7, a level 1 alarm is triggered. For example, when the flow rate is 12.5 L / min, the theoretical pressure is 12.5 × 0.1 + 3.0 = 4.25 MPa, and the measured pressure is 3.08 MPa. The difference of 1.17 MPa corresponds to D = 0.975, which exceeds the threshold of 0.7. A deviation data packet [timestamp, 0.9, 12.7, 3.19] is generated. When D > 0.7 for three consecutive time slices, the sprinkler system self-test program is activated, and the current deviation of 0.9 is recorded in the anomaly database.

[0078] The thermal imbalance derivation submodule uses the temperature and pressure deviation and the roll gap cooling water flow value, accumulates the deviation and flow value in a time series, and superimposes the pressure accumulation effect caused by insufficient flow. The total pressure imbalance per unit time is calculated to generate the roll gap hot tank thermal imbalance coefficient that quantifies the degree of cooling anomaly.

[0079] Extract the temperature and pressure deviation sequence [0.9, 0.85, 0.88, 0.82] and the corresponding flow sequence [12.7, 12.6, 12.5, 12.4] L / min within the 40ms time window 1640000000.123456 to 1640000000.123496, and set the rated flow rate Q 额定 =15L / min, calculate the flow rate deficiency coefficient for each time slice For example, when Q0 = 12.7, β0 = 1-12.7 / 15 = 0.153, and the pressure imbalance E of a single time slice is calculated. i =D i ×β i , the sequence is [0.9×0.153=0.1377,0.85×0.16=0.136,0.88×0.1667=0.1467,0.82×0.1733=0.1421], the total amount of the four time slices is 0.1377+0.136+0.1467+0.1421=0.5625, the time base is set to T=10s, the thermal imbalance coefficient When K>0.05, it is determined to be a continuous thermal imbalance. For example, if the K value continues to increase to 0.06 in the subsequent three time slices, a secondary alarm is triggered and the roller press speed is reduced by 5%. A thermal imbalance coefficient of 0.05625 and associated control instructions are generated to the actuator queue.

[0080] See also Figure 5 , the sealing pressure threshold module includes:

[0081] The reverse correlation quantification submodule calls the thermal imbalance coefficient of the roll gap hot stuffy tank, extracts the time series data of the hot stuffy tank pressure accumulation rate and cooling water flow, calculates the negative correlation slope of the pressure rate with the flow rate, and generates a reverse correlation factor that describes how the flow rate suppresses the pressure growth rate.

[0082] Call the thermal imbalance coefficient of the roller gap hot stuffy tank 0.05625, extract the pressure accumulation rate sequence [0.020, 0.018, 0.019, 0.017] MPa / s (interval 10ms) in the time window 16400000000.123456 to 1640000000.123496, and synchronously obtain the corresponding cooling water flow sequence [12.7, 12.6, 12.5, 12.4] L / min to calculate the mean pressure rate. Traffic mean Calculate flow deviation point by point The pressure rate deviation is [+0.15, +0.05, -0.05, -0.15] L / min. We get [+0.0015,-0.0005,+0.0005,-0.0015]MPa / s, covariance

[0083] Flow standard deviation Pressure rate standard deviation Correlation coefficient Negative correlation slope Verification example: When the flow rate drops from 12.7L / min to 12.4L / min (ΔQ = -0.3L / min), the pressure rate increases from 0.020 to 0.017MPa / s (ΔV_p = +0.003MPa / s), calculate the slope Compared with the calculated value of -0.00106, when |S| < 0.002 is determined, it is marked as a weak correlation, and a reverse correlation factor of -0.00106 is generated and written into the correlation database field Corr_Factor_7.

[0084] The pressure limit matching submodule, based on the reverse correlation factor, calls the maximum pressure strength data of the seal ring, matches the difference between the current pressure accumulation rate and the pressure limit value of the seal ring, calculates the risk probability of the pressure growth exceeding the limit per unit time, and generates a pressure limit threshold that reflects the risk of seal failure;

[0085] Based on the reverse correlation factor -0.00106, the limit parameters of the sealing ring model SC-5 are called: maximum compressive strength P max =5.0MPa (based on material tensile strength σ_b = 600MPa × safety factor 0.8), current pressure value P current =3.2MPa, pressure accumulation rate V p =0.0185MPa / s, calculate the remaining time Risk Probability Set the risk threshold R th =0.01s-1 (according to the equipment maintenance regulations: the allowed risk accumulation value per hour is ≤36), the risk difference ΔR is calculated as 0.01027-0.01=0.00027, and an early warning is triggered when ΔR>0, for example, when P current =4.5MPa and V p =0.02MPa / s, T remain =(5.0-4.5) / 0.02=25 seconds, R=0.04s-1, at this time ΔR=0.03 triggers the third-level alarm, the current risk value 0.01027 generates the warning code WARN_007, associates the sealing ring ID SC-5-203, generates the pressure limit threshold 0.01027s-1, and writes it to the 203rd row of the risk log table Risk_Log.

[0086] The threshold correction submodule uses the pressure limit threshold and the flow value of the roll gap cooling water branch to convert the flow value into a pressure suppression coefficient according to the inverse correlation factor. It then adds the correction weight of the current thermal imbalance coefficient on the pressure accumulation, dynamically adjusts the temperature alarm boundary value, and generates a roll nip area temperature safety threshold that adapts to the working conditions in real time.

[0087] Call the pressure limit threshold of 0.01027s-1 and the current branch flow of 12.7L / min, calculate the pressure suppression coefficient C = Q×|S| = 12.7×0.00106 = 0.01346MPa / s (where S = -0.00106), set the thermal imbalance coefficient weight α = 0.6 (based on historical fault data regression analysis), the pressure suppression coefficient weight β = 0.4, calculate the comprehensive correction amount ΔT = α×K + β×C = 0.6×0.05625+0.4×0.01346=0.03375+0.00538=0.03913, the original temperature alarm threshold T base =150℃ (equipment rated upper limit), adjusted threshold T new =T base -ΔT×100=150-3.913=146.087℃, for example, when the flow rate drops to 12.0L / min, C=12.0×0.00106=0.01272, ΔT=0.6×0.05625+0.4×0.01272=0.03375+0.00509=0.03884, T new=150-3.884=146.116°C, dynamically written to the PLC register address 0x305A (data type Float, value 146.087), synchronously updated the alarm threshold display area of the HMI interface, generated the real-time roller nip zone temperature safety threshold of 146.087°C, and triggered the threshold change event Event_Threshold_Update to the monitoring center.

[0088] See also Figure 6 , the roller pressure abnormality alarm module includes:

[0089] The threshold comparison submodule calls the real-time cooling water temperature value of the roller pressing four-dimensional parameter set to obtain the roller pressing zone temperature safety threshold, compares the temperature sampling data with the threshold range frame by frame, counts the number of consecutive time windows in which the temperature exceeds the threshold, and generates an over-limit status indicator reflecting the temperature over-limit status;

[0090] Call the cooling water temperature sequence [146.5, 147.0, 147.8, 148.3, 148.9]°C within the 40ms range of the timestamp 1640000000.123456 to 1640000000.123496 of the Pipe_203 branch in the roller pressing four-dimensional parameter set. The temperature sampling interval is 10ms. Read the dynamic temperature safety threshold field T threshold =146.087℃ (stored in PLC register address 0x305A), frame by frame comparison: 146.5-146.087=0.413>0 is marked as exceeding the standard, 147.0-146.087=0.913>0 is marked as exceeding the standard, 147.8-146.087=1.713>0 is marked as exceeding the standard, 148.3-146.087=2.213>0 is marked as exceeding the standard, 148.9-146.087=2.813>0 is marked as exceeding the standard, and the number of consecutive exceeding windows is counted. Set each 10ms as 1 window. Currently, there are 5 consecutive windows. Continuous exceeding of the standard. When the number of consecutive exceeding of the standard is ≥ 3, the status flag is activated. For example, when the temperature sequence is [145.5, 146.2, 146.0, 147.1, 147.5]℃, the exceeding mark is [0, 0, 0, 1, 1]. Continuous exceeding of the standard in only two windows does not trigger the flag. The current exceeding of the standard in five windows generates the exceeding state flag Flag = 1 (binary value 0b1), which is written to bit 3 of the status register address 0x4080, and the exceeding duration t = 50ms is synchronously recorded in the log file / var / log / overheat_203.log.

[0091] The abnormality positioning submodule, based on the excessive state identifier, calls the data on the excessive pressure of the hot and stuffy tank and the location parameters of the roller gap spray branch, calculates the linear correlation coefficient between the duration of the temperature excess and the pressure increase, determines the probability weight of the abnormal source being the spray branch or the cooling pipeline, and generates a continuous excessive coefficient including the abnormal area mark;

[0092] Based on Flag = 1, extract the hot and stuffy tank pressure exceeding the standard amplitude data series [0.018, 0.019, 0.020, 0.021, 0.022] MPa / s (time window 16400000000.123456-16400000000.123496), associate it with the position parameters of the spray branch PID_203 (three-dimensional coordinates x = 1250mm, y = 780mm, z = 320mm), calculate the covariance of the pressure increase series corresponding to the 5 windows (50ms) of temperature exceeding the standard duration, temperature series T = [146.5, 147.0, 147.8, 148.3, 148.9], pressure increase ΔP = [0.018, 0.019, 0.020, 0.021, 0.022], and calculate the temperature mean 147.7℃, average pressure increase Temperature deviation ΔT i =[-1.2,-0.7,+0.1,+0.6,+1.2], pressure deviation ΔP i =[-0.002,-0.001,0.000,+0.001,+0.002], covariance

[0093] Temperature standard deviation

[0094] Pressure standard deviation Correlation coefficient When r>1.0, it is determined to be a strong positive correlation, and the probability weight of the sprinkler branch abnormality is W p =0.8 (preset: sprinkler failure history accounts for 80%), cooling pipeline abnormality probability W c =0.2, calculate the continuous exceedance coefficient CS = 0.8×3.98+0.2×0.020=3.184+0.004=3.188, when CS≥2.5, mark the abnormal source as the sprinkler branch, generate the positioning result Loc_Result=203 (coding rule: 200+branch number), and write it into the 203rd row of the positioning database table Location_Fault.

[0095] The alarm generation submodule calls the continuous exceeding coefficient, extracts the spray branch position code and the pressure exceeding value of the hot stuffy tank, matches the abnormal area mark and the pressure increase according to the preset alarm rules, constructs a mapping relationship between the abnormal type and level, and generates a slag roller cooling failure alarm instruction including the position code and pressure amplitude;

[0096] Call the continuous exceeding coefficient CS=3.188, extract the spray branch position code PID_203 (mapped to the equipment name "roll gap left spray group-203") and the current pressure increase ΔP=0.022MPa / s, match the Level-2 trigger condition in the alarm rule table Rule_Table: ΔP≥0.02MPa / s and CS≥2.5, current ΔP=0.022>0.02 and CS=3.188>2.5, query the alarm level mapping relationship: Level-2 corresponds to "Secondary Alarm: Insufficient Spray Flow", construct the alarm instruction JSON structure, including the alarm ID (timestamp 1640000000+branch number 203), location information (coordinates 1250,780,320), pressure increase 0.022, alarm level 2, For example, the alarm content is {"AlarmID":"1640000000_123496_203","Location":"Roll gap left spray group -203","Coord":"(1250,780,320)","ΔP":0.022,"Level":2}. It is written to the end offset 0x5000 of the alarm queue Buffer_Alarm and synchronously sent to the third partition of the HMI alarm panel in the central control room (IP address 192.168.3.15 port 502). The real-time alarm counter Counter_Alarm is updated from 17 to 18, and the alarm log is stored in / var / log / alarm_203.log. The record fields include timestamp, branch number, pressure increase, and alarm level.

[0097] A method for alarming abnormal cooling water of a hot roller press during steel slag pressing comprises the following steps:

[0098] S1: Monitor the flow rate and injection temperature of the cooling water branch in the roll gap of the roll press area, collect the cooling water pressure value in the hot stuffy tank and the vibration amplitude value of the roll press bearing, align each type of parameter by time stamp and integrate them into a unified time series to generate a four-dimensional roll press parameter set;

[0099] S2: Based on the four-dimensional parameter set of roller pressing, the coordinates of the roller spray port position and the water inlet valve of the hot stuffy tank are extracted, and the dynamic mapping relationship between the roller gap flow, hot stuffy tank pressure and bearing vibration amplitude is established to generate the hot stuffy tank topological association diagram;

[0100] S3: Call the roller gap injection temperature value and the hot stuffy tank pressure value in the roller pressing four-dimensional parameter set, calculate the standard deviation and mean offset of the two in the time series dimension, and generate the roller gap hot stuffy tank thermal imbalance coefficient;

[0101] S4: Based on the thermal imbalance coefficient of the roll gap hot stuffy tank and the preset hot stuffy tank sealing ring pressure limit value, combined with the current roll gap cooling water branch flow value, the temperature judgment boundary is dynamically adjusted using the linear interpolation method to generate the roll nip area temperature safety threshold;

[0102] S5: Based on the real-time roll gap cooling water injection temperature value in the roll pressing four-dimensional parameter set and the roll pressing zone temperature safety threshold, the over-limit frequency statistics within the continuous time window are performed. When the alarm condition is triggered, the slag roll pressing cooling failure alarm instruction is generated.

[0103] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A cooling water abnormality alarm system for hot rolling of steel slag, characterized in that: The system comprises: The roll nip parameter monitoring module collects the flow rate and injection temperature of the roll gap cooling water branch, obtains the cooling water pressure value in the hot stuffy tank, monitors the vibration amplitude of the roll bearing, aligns each parameter type by time stamp, and generates a four-dimensional roll parameter set; The hot stuffy tank topology association module associates the coordinates of the hot stuffy tank water inlet valve with the position of the roller spray port based on the roller pressing four-dimensional parameter set, establishes a real-time mapping relationship between the roller gap flow, the hot stuffy tank pressure and the bearing vibration, and generates a hot stuffy tank topology association diagram; The spray failure reasoning module integrates the four-dimensional roll pressure parameter set and the hot stuffy tank topology association diagram, calculates the deviation between the roll gap spray temperature and the hot stuffy tank pressure, and generates the roll gap hot stuffy tank thermal imbalance coefficient; The sealing pressure threshold module matches the thermal imbalance coefficient of the roll gap hot stuffy tank with the pressure limit value of the hot stuffy tank seal ring, dynamically modifies the temperature alarm threshold according to the current roll gap cooling water branch flow value, and generates a roll nip area temperature safety threshold; The roller pressing abnormality alarm module calls the real-time roller gap cooling water injection temperature value in the roller pressing four-dimensional parameter set, performs time series continuity judgment with the roller pressing area temperature safety threshold, and generates a slag roller pressing cooling failure alarm instruction.

2. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The four-dimensional parameter set of rolling includes the roll gap flow timing sequence, the injection temperature timing sequence, the tank pressure timing sequence, and the bearing vibration timing sequence. The hot stuffy tank topology association diagram specifically includes the valve port spray coordinate mapping relationship, the flow pressure dynamic association matrix, and the vibration pressure conduction topology path. The thermal imbalance coefficient of the roll gap hot stuffy tank includes the temperature and pressure dynamic deviation rate, the heat conduction gradient difference, and the heat exchange attenuation factor. The temperature safety threshold of the roll pressure area is specifically the dynamic threshold range, the pressure flow coupling coefficient, and the sealing ring deformation critical value. The slag roll pressing cooling failure alarm instruction includes the temperature limit interval mark, the cooling interruption timing positioning, and the spray failure trigger signal type.

3. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The roller nip parameter monitoring module includes: The data acquisition submodule synchronously collects the cooling water injection temperature value from the temperature sensor, the branch flow value from the electromagnetic flowmeter, the tank water pressure value from the pressure sensor, and the bearing vibration amplitude value from the vibration sensor. It stores the four types of parameters according to independent time stamps and generates an original parameter set containing temperature, flow, pressure, and vibration. The timing alignment submodule calls the parameter timestamps in the original parameter set, aligns the sampling points of the temperature, flow, and pressure values according to a unified time reference, constrains the time difference between the vibration value and the temperature value to a preset range, extracts the four types of parameters within the synchronization time window, and generates a synchronization parameter sequence with a time stamp; The parameter fusion submodule interpolates the temperature, flow, and pressure values in the synchronized parameter sequence to fill in the missing data, smoothes and denoises the vibration values, aligns the four types of parameters into vectors of equal length according to timestamps, integrates them into multidimensional data units, and generates a four-dimensional roller pressing parameter set with time stamps.

4. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The hot tank topology association module includes: The coordinate association submodule calls the branch flow value in the roller pressing four-dimensional parameter set, extracts the roller pressing roller spray port position coordinates and the hot stuffy tank water inlet valve coordinates, matches the spatial distribution relationship of the two coordinates, establishes the pipeline connection mapping between the spray port and the water inlet valve, and generates a coordinate mapping table containing the position correspondence relationship; The weight calculation submodule associates the time series data of the branch flow value and the hot and stuffy tank pressure value based on the pipeline connection relationship in the coordinate mapping table, calculates the matching degree of the fluctuation trend of the flow value and the pressure value, generates a proportional factor based on the pipeline length and cross-sectional parameters, quantifies the influence weight of the flow on the pressure, and generates a linear correlation weight coefficient; The topology generation submodule calls the linear correlation weight coefficient and the bearing vibration value in the rolling four-dimensional parameter set, superimposes the vibration amplitude and weight coefficient according to the pipeline node, constructs a three-dimensional relationship matrix of flow-pressure-vibration, arranges the matrix units according to the loop path connection rules, and generates a hot and stuffy tank topology association diagram including the node association strength.

5. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The spray failure reasoning module includes: The pressure change quantification submodule calls the real-time data of the roller gap cooling water injection temperature in the roller pressing four-dimensional parameter set, obtains the flow and pressure association weights in the hot tank topology association diagram, calculates the pressure change gradient corresponding to the unit flow increment, and generates the unit pressure change of the flow pressure change; The deviation amplitude calculation submodule extracts the current flow value and the actual hot and stuffy tank pressure value based on the unit pressure change, calculates the theoretical matching curve of the injection temperature and pressure value, compares the absolute value of the difference between the measured temperature and the theoretical curve, and generates a temperature and pressure deviation degree that reflects the degree of temperature and pressure deviation; The thermal imbalance derivation submodule calls the temperature and pressure deviation and the roll gap cooling water flow value, accumulates the deviation and flow value in a time series, superimposes the pressure accumulation effect caused by insufficient flow, calculates the total pressure imbalance per unit time, and generates the roll gap hot stuffy tank thermal imbalance coefficient that quantifies the degree of cooling abnormality.

6. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The sealing pressure threshold module includes: The reverse correlation quantification submodule calls the thermal imbalance coefficient of the roll gap hot stuffy tank, extracts the time series data of the hot stuffy tank pressure accumulation rate and the cooling water flow rate, calculates the negative correlation slope of the pressure rate with the flow rate, and generates a reverse correlation factor describing the flow rate suppressing the pressure growth rate; The pressure limit matching submodule, based on the reverse correlation factor, calls the maximum pressure strength data of the sealing ring, matches the difference between the current pressure accumulation rate and the pressure limit value of the sealing ring, calculates the risk probability of the pressure growth exceeding the limit per unit time, and generates a pressure limit threshold reflecting the risk of seal failure; The threshold correction submodule calls the pressure limit threshold and the flow value of the roll gap cooling water branch, converts the flow value into a pressure suppression coefficient according to the inverse correlation factor, superimposes the correction weight of the current thermal imbalance coefficient on the pressure accumulation, dynamically adjusts the temperature alarm boundary value, and generates a roll nip area temperature safety threshold that adapts to the working conditions in real time.

7. The abnormal alarm system for cooling water during hot rolling of steel slag according to claim 1 is characterized by: The roller pressure abnormality alarm module includes: The threshold comparison submodule calls the real-time cooling water temperature value of the roller pressing four-dimensional parameter set to obtain the roller pressing zone temperature safety threshold, compares the temperature sampling data with the threshold range frame by frame, counts the number of consecutive time windows in which the temperature exceeds the threshold, and generates an over-limit status indicator reflecting the temperature over-limit status; The abnormality positioning submodule, based on the excessive state identifier, calls the data on the excessive pressure of the hot and stuffy tank and the location parameters of the roller gap spray branch, calculates the linear correlation coefficient between the duration of the temperature excess and the pressure increase, determines the probability weight of the abnormal source being the spray branch or the cooling pipeline, and generates a continuous excessive coefficient including the abnormal area mark; The alarm generation submodule calls the continuous exceeding coefficient, extracts the spray branch position code and the exceeding pressure of the hot stuffy tank, matches the abnormal area mark and the pressure increase according to the preset alarm rules, constructs a mapping relationship between the abnormal type and the level, and generates a slag roller cooling failure alarm instruction including the position code and the pressure amplitude.

8. A method for alarming abnormal cooling water during hot rolling of steel slag, characterized in that: The method is used in the steel slag hot roller pressing cooling water abnormality alarm system according to any one of claims 1 to 7, comprising the following steps: S1: Monitor the flow rate and injection temperature of the cooling water branch in the roll gap of the roll press area, collect the cooling water pressure value in the hot stuffy tank and the vibration amplitude value of the roll press bearing, align each type of parameter by time stamp and integrate them into a unified time series to generate a four-dimensional roll press parameter set; S2: Based on the four-dimensional roller pressing parameter set, the roller spray port position coordinates and the hot stuffy tank water inlet valve coordinates are extracted, a dynamic mapping relationship between the roller gap flow, hot stuffy tank pressure and bearing vibration amplitude is established, and a hot stuffy tank topology association diagram is generated; S3: calling the roll gap injection temperature value and the hot stuffy tank pressure value in the roll pressing four-dimensional parameter set, calculating the standard deviation and mean offset of the two in the time series dimension, and generating the roll gap hot stuffy tank thermal imbalance coefficient; S4: Based on the thermal imbalance coefficient of the roll gap hot stuffy tank and the preset pressure limit value of the hot stuffy tank sealing ring, combined with the current flow value of the roll gap cooling water branch, the temperature judgment boundary is dynamically adjusted using a linear interpolation method to generate a temperature safety threshold of the roll nip area; S5: Based on the real-time roll gap cooling water injection temperature value in the roll pressing four-dimensional parameter set and the roll pressing zone temperature safety threshold, the over-limit frequency statistics within the continuous time window are performed. When the alarm condition is triggered, a slag roll pressing cooling failure alarm instruction is generated.

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