CN115111580A - Quantitative control method for slag cooler - Google Patents
Quantitative control method for slag cooler Download PDFInfo
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- CN115111580A CN115111580A CN202210671357.7A CN202210671357A CN115111580A CN 115111580 A CN115111580 A CN 115111580A CN 202210671357 A CN202210671357 A CN 202210671357A CN 115111580 A CN115111580 A CN 115111580A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23C—METHODS OR APPARATUS FOR COMBUSTION USING FLUID FUEL OR SOLID FUEL SUSPENDED IN A CARRIER GAS OR AIR
- F23C10/00—Fluidised bed combustion apparatus
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- F23C10/28—Control devices specially adapted for fluidised bed, combustion apparatus
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
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Abstract
The application discloses a quantitative control method for a slag cooler, which comprises the following steps: acquiring production data and material layer pressure difference of each sampling time point, and recording the production data as stable data when the maximum difference value of the production data in a sampling time period is less than or equal to a first stable threshold value; calculating the sampling average value of the adjustment quantity of the slag cooler in each group of stable data and the material layer pressure difference change rate; respectively calculating the maximum difference value of the coal feeder regulating quantity and the primary fan regulating quantity in two adjacent groups of stable data, and calculating the variable quantity of the regulating quantity of the slag cooler and the material layer differential pressure change rate in the two adjacent groups of stable data when the two regulating quantities are less than or equal to a second stable threshold value; generating a fitting curve according to the adjustment quantity of the slag cooler and the variation quantity of the material layer differential pressure variation rate; and determining the adjustment quantity of the target slag cooler on the fitting curve according to the target value of the change rate of the pressure difference of the given material bed. Through the technical scheme in this application, solved the poor problem of current cold sediment machine bottom sediment discharge capacity control accuracy.
Description
Technical Field
The application relates to the technical field of slag coolers, in particular to a quantitative control method of a slag cooler.
Background
For a circulating fluidized bed boiler, in order to ensure continuous and safe operation of the boiler, control the bed pressure of a hearth, prevent large-particle material deposition and coking in the boiler and maintain good fluidization conditions, slag must be discharged timely. The slag cooler is used as a key auxiliary device for discharging the bottom slag, and plays a key role in controlling the continuous discharge of the bottom slag, recovering the heat of the bottom slag, reducing the temperature of the bottom slag, reducing the thermal pollution and the like.
At present, the main control method of the slag cooler is to measure the thickness of a bottom slag layer to be discharged, perform PID control operation through a Distributed Control System (DCS), send a control signal of an adjustment quantity of the slag cooler to a programmable logic control system PLC, and control the opening of a slag discharge door of the slag cooler by the PLC, thereby realizing the control of the slag discharge quantity.
In the prior art, the method only simply controls by measuring the thickness of the material layer, and does not consider factors influencing the thickness of the material layer. For example: the primary air quantity influences the thickness of a material layer, when the material layer pressure difference is changed, if a primary fan is just adjusted, the material layer pressure difference is in an unstable state, and the problem of inaccurate bottom slag discharge exists when the material layer pressure difference is used for controlling slag cooling; another example is: the coal feeding quantity can also influence the thickness of a material layer, if the material layer pressure difference is changed, after the coal is fed by the coal feeder, the material layer pressure difference is also in an unstable state, the thickness of the material layer can be changed, and the quantitative control precision of the discharge capacity of bottom slag of the slag cooler is further influenced.
Meanwhile, the PID feedback control method has the problem of time lag, and the condition of untimely slag discharge possibly exists, so that the boiler operation is influenced; except the PID feedback control method, PID parameter adjustment is needed according to parameters of different boilers, and because the PID feedback control method controls the slag cooler through the target material layer pressure difference through the coefficients of a proportional term, an integral term and a differential term, the slag cooler of each boiler has respective characteristics, the value of each coefficient of the PID can be determined through a large amount of debugging work, and the defects that early-stage debugging is needed, the workload is large, and self-learning cannot be achieved exist.
Disclosure of Invention
The purpose of this application lies in: the method solves the problems of poor control accuracy and time lag of the bottom slag discharge of the slag cooler based on the thickness of the material layer, and realizes a feed-forward quantitative control method.
The technical scheme of the application is as follows: the quantitative control method for the slag cooler comprises the following steps: step 1, acquiring production data of a boiler at each sampling time point and corresponding material layer pressure difference, and recording the production data in a sampling time period as a group of stable data when the maximum difference value of the production data in the sampling time period is judged to be less than or equal to a first stable threshold value, wherein the production data at least comprises the adjustment quantity of a slag cooler, the adjustment quantity of a coal feeder and the adjustment quantity of a primary air fan; step 2, calculating the sampling average value of the adjustment quantity of the slag cooler in each group of stable data and the material layer pressure difference change rate of the material layer pressure difference corresponding to the sampling time period; step 3, respectively calculating the maximum coal feeder difference value of the coal feeder regulating quantity and the maximum fan difference value of the primary fan regulating quantity in the two adjacent groups of stable data, when the maximum coal feeder difference value and the maximum fan difference value are judged to be smaller than or equal to a second stable threshold value, calculating the difference value of the two adjacent groups of stable data corresponding to the sampling average value, recording the variation quantity of the regulating quantity of the slag cooler, and calculating the variation quantity of the corresponding material layer pressure difference variation rate; step 4, grouping and aggregating data according to the regulating quantity change quantity of the slag cooler and the material layer differential pressure change rate change quantity, and generating a differential pressure-regulating quantity curve in a fitting mode; and 5, determining the adjustment quantity of the target slag cooler on a pressure difference-adjustment quantity curve according to the target value of the variation rate of the pressure difference of the material bed, wherein the adjustment quantity of the target slag cooler is used for controlling the bottom slag discharge of the slag cooler.
In any one of the above technical solutions, further, step 1 further includes: judging whether the maximum difference value of each production data in a sampling time period is less than or equal to a first stable threshold value, wherein the process specifically comprises the following steps: respectively selecting the maximum value and the minimum value of each production data in a sampling time period, recording the difference value between the maximum value and the minimum value as the maximum difference value, and calculating the average value of each production data; calculating the product of the average value and the fluctuation ratio, and recording the product as a first stable threshold value; and judging whether the maximum difference value is smaller than or equal to a first stable threshold value, if so, recording each production data in a sampling time period as a group of stable data, and if not, deleting each production data in the sampling time period.
In any one of the above technical solutions, further, in step 2, calculating a material bed pressure difference change rate corresponding to the material bed pressure difference in the sampling time period specifically includes: selecting pressure difference starting data and pressure difference ending data corresponding to the material layer pressure difference within a preset time window range at the beginning and the end of the sampling time period respectively; respectively calculating a first average value of the pressure difference starting data and a second average value of the pressure difference ending data; and calculating the change rate of the material layer pressure difference according to the difference value between the first average value and the second average value.
In any one of the above technical solutions, further, the second smooth threshold includes a coal feeder smooth threshold and a fan smooth threshold, and step 3 specifically includes: respectively selecting the maximum value and the minimum value of the coal feeder regulating quantity and the primary fan regulating quantity in two adjacent groups of stable data, calculating the difference value between the maximum value and the minimum value in the coal feeder regulating quantity, recording the difference value as the maximum coal feeder difference value, calculating the difference value between the maximum value and the minimum value of the primary fan regulating quantity, and recording the difference value as the maximum fan difference value; calculating the average value of the adjustment quantity of the coal feeder and the average value of the adjustment quantity of the primary air fan, recording the product of the average value of the adjustment quantity of the coal feeder and the fluctuation ratio as the stable threshold value of the coal feeder, and recording the product of the average value of the adjustment quantity of the primary air fan and the fluctuation ratio as the stable threshold value of the air fan; and judging whether the maximum difference value of the coal machine is smaller than or equal to a stable threshold value of the coal machine and whether the maximum difference value of the fan is smaller than or equal to a stable threshold value of the fan, if so, calculating the difference value of the two adjacent groups of stable data corresponding to the sampling average value, recording the variation of the adjustment quantity of the slag cooler, calculating the variation of the corresponding material layer pressure difference variation rate, and if not, deleting the two adjacent groups of stable data.
In any one of the above technical solutions, further, in step 3, the method further includes: and when the adjustment quantity change quantity of the slag cooler or the material layer pressure difference change rate change quantity is judged to be smaller than a preset threshold value, deleting the adjustment quantity change quantity of the slag cooler and the corresponding material layer pressure difference change rate change quantity.
In any one of the above technical solutions, further, step 4 specifically includes: step 41, sequencing the quantity of change of the regulating quantity of the slag cooler, grouping and aggregating data of the sequenced quantity of change of the regulating quantity of the slag cooler according to a preset numerical interval, and recording the grouped data as a regulating quantity fitting data group; step 42, calculating the median of the variation of the material layer differential pressure variation rate corresponding to any one group of adjustment quantity fitting data group, recording the median as differential pressure fitting data, calculating the median of the adjustment quantity variation of the slag cooler corresponding to the adjustment quantity fitting data group, and recording the median as adjustment quantity fitting data; and 43, generating a pressure difference-regulating quantity curve by adopting a fitting mode according to the regulating quantity fitting data and the pressure difference fitting data.
In any one of the above technical solutions, further, step 41 further includes: and deleting the adjustment quantity fitting data group of which the data number is less than the number threshold value in the adjustment quantity fitting data group.
The beneficial effect of this application is:
technical scheme in this application, the main factor that influences bed of material thickness has been considered, the regulation of primary air fan and the regulation of feeder, and combine the rate of change of bed of material pressure difference and the regulating variable of cold sediment machine, judge and the grouping polymerization steadily through the data, utilize the feedforward mode of model prediction to obtain the quantitative regulating variable of cold sediment machine, it only considers bed of material thickness to have compensatied current cold sediment machine control, lead to the not accurate not enough of regulating variable, current feedback control's time lag problem has effectively been solved, and can adapt to different boilers automatically, there is not PID control's cold start-up problem.
Drawings
The advantages of the above and/or additional aspects of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow diagram of a method of quantitative control of a slag cooler according to an embodiment of the present application;
FIG. 2 is a schematic view of the scatter plot between the variation of the rate of change of the material bed differential pressure and the variation of the slag cooler adjustment according to an embodiment of the present application;
FIG. 3 is a schematic plot of the scatter plot between the change rate of the differential pressure of the bed of material after polymerization and the change in the adjustment of the slag cooler according to one embodiment of the present application;
FIG. 4 is a schematic plot of scatter between variation in rate of change of material bed differential pressure and variation in slag cooler adjustment with a model fit line according to one embodiment of the present application;
FIG. 5 is a data trend graph of actual slag cooler adjustment variation data according to one embodiment of the present application;
fig. 6 is a model predicted slag cooler adjustment variation data trend graph according to one embodiment of the present application.
Detailed Description
In order that the above objects, features and advantages of the present application can be more clearly understood, the present application will be described in further detail with reference to the accompanying drawings and detailed description. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited by the specific embodiments disclosed below.
As shown in fig. 1, the present embodiment provides a quantitative control method for a slag cooler, including:
step 1, acquiring production data of a boiler at each sampling time point and corresponding material layer pressure difference, and recording the production data in a sampling time period as a group of stable data when the maximum difference value of the production data in the sampling time period is judged to be less than or equal to a first stable threshold value, wherein the production data at least comprises the adjustment quantity of a slag cooler, the adjustment quantity of a coal feeder and the adjustment quantity of a primary air fan;
specifically, the production data selected in this embodiment includes parameters such as a coal feeder adjustment amount C, a primary air fan adjustment amount F, a slag cooler adjustment amount S, and the like, and these parameters and the material layer pressure difference P can be read by the DCS system. In the process of reading the data, each data can correspond to one sampling time point, and therefore, the data can correspond to one another in the time dimension.
It should be noted that the implementation of the DCS system is not limited in this embodiment.
Therefore, the production data and the material layer pressure difference P corresponding to the sampling time points in each sampling time period can be obtained in a data reading mode.
Further, step 1 further comprises: judging whether the maximum difference value of each production data in a sampling time period is less than or equal to a first stable threshold value, wherein the process specifically comprises the following steps: respectively selecting the maximum value and the minimum value of each production data in a sampling time period, recording the difference value between the maximum value and the minimum value as the maximum difference value, and calculating the average value of each production data; calculating the product of the average value and the fluctuation ratio, and recording the product as a first stable threshold value; and judging whether the maximum difference value is smaller than or equal to a first smooth threshold value, if so, judging that the production data in the sampling time period are smooth, recording all the production data in one sampling time period as a group of smooth data, otherwise, judging that the production data in the sampling time period are not smooth, and deleting all the production data in the sampling time period.
Specifically, when judging whether the production data in a certain sampling time period is steady, the production data that need use can include feeder regulating variable C, primary air fan regulating variable F, cold sediment machine regulating variable S, only when these data all satisfy the steady judgement condition of data, just the production data of this sampling time period in is steady, and corresponding steady data judgement condition is:
max(x)-min(x)≤mean(x)×n％
in the formula, x is a selected data field, and may be a coal feeder adjustment amount C, a primary air fan adjustment amount F, a slag cooler adjustment amount S, max (x), min (x), mean (x) are respectively a maximum value, a minimum value, and an average value in the data field, wherein the calculation process of the average mean (x) is not described again. n% is fluctuation ratio and is set value.
That is, the above production data is smoothly defined as: and in the time length (t) of a certain sampling time period, when the coal feeder regulating quantity C, the primary air fan regulating quantity F and the slag cooler regulating quantity S are judged to simultaneously meet the stable data judgment condition, the production data of the section is a stable data section.
Step 2, calculating the sampling average value of the adjustment quantity S of the slag cooler in each group of stable data and the material layer pressure difference change rate of the material layer pressure difference P corresponding to the sampling time period; the sampling average value of the slag cooler regulating variables S is the ratio of the sum of the regulating variables S of each slag cooler in the set of stable data to the number of the data.
Further, in step 2, the calculation of the change rate is smoothed by using a time window to eliminate data jump of the material bed pressure difference, so that the material bed pressure difference change rate corresponding to the material bed pressure difference P in the sampling time period specifically includes:
selecting pressure difference starting data and pressure difference ending data corresponding to the material layer pressure difference P in a preset time window range at the beginning and the end of the sampling time period respectively;
respectively calculating a first average value of the pressure difference starting data and a second average value of the pressure difference ending data;
and calculating the change rate of the material layer pressure difference according to the difference value between the first average value and the second average value.
Specifically, the preset time window range can be set to include 3 sampling time points, three material layer pressure differences can be respectively selected at the beginning and the end of the sampling time period, and the three material layer pressure differences are sequentially recorded as pressure difference starting data (p) 1 、p 2 、p 3 ) And pressure difference end data (p) n-3 、p n-2 、p n-1 ) Wherein n is the number of sampling time points in the sampling time period, and the first piece of data p is not included in the selected pressure difference starting data 0 The last data p is not included in the pressure difference ending data n 。
Then, the material layer pressure difference change rate can be calculated according to a corresponding calculation formula, and the corresponding calculation formula is as follows:
in the formula, V p Mean (p) is the rate of change of the differential pressure of the bed n-3 、p n-2 、p n-1 ) Mean (p) of the end of differential pressure data 1 、p 2 、p 3 ) Average of the pressure difference start data, t n-2 、t 2 The sampling time points of the pressure difference P of the material layer at the end and the beginning are shown.
Further, the step 3 specifically includes:
respectively selecting the maximum value and the minimum value of the coal feeder regulating quantity and the primary fan regulating quantity in two adjacent groups of stable data, calculating the difference value between the maximum value and the minimum value in the coal feeder regulating quantity, recording the difference value as the maximum coal feeder difference value, calculating the difference value between the maximum value and the minimum value of the primary fan regulating quantity, and recording the difference value as the maximum fan difference value;
calculating the average value of the adjustment quantity of the coal feeder and the average value of the adjustment quantity of the primary air fan, recording the product of the average value of the adjustment quantity of the coal feeder and the fluctuation ratio as the stable threshold value of the coal feeder, and recording the product of the average value of the adjustment quantity of the primary air fan and the fluctuation ratio as the stable threshold value of the air fan;
and judging whether the maximum difference value of the coal machine is smaller than or equal to a stable threshold value of the coal machine and whether the maximum difference value of the fan is smaller than or equal to a stable threshold value of the fan, if so, calculating the difference value of the two adjacent groups of stable data corresponding to the sampling average value, recording the variation of the adjustment quantity of the slag cooler, calculating the variation of the corresponding material layer pressure difference variation rate, and if not, deleting the two adjacent groups of stable data. .
Specifically, the stable data judgment conditions are utilized to judge the stable data of the coal feeder regulating quantity and the primary air fan regulating quantity in the two adjacent groups of stable data, the calculation of the regulating quantity and the material layer pressure difference change rate change quantity of the slag cooler is only carried out when the coal feeder regulating quantity and the primary air fan regulating quantity are stable, and otherwise, the current stable data is skipped to calculate the next two adjacent groups of stable data.
Preferably, step 3 further comprises: and when the adjustment quantity change quantity of the slag cooler or the material layer pressure difference change rate change quantity is judged to be smaller than a preset threshold value, deleting the adjustment quantity change quantity of the slag cooler and the corresponding material layer pressure difference change rate change quantity. The preset threshold value is data close to 0, namely data close to 0 in the adjustment quantity variation quantity of the slag cooler and the corresponding material layer differential pressure variation rate variation quantity are filtered.
In this embodiment, the calculation formula of the adjustment amount variation of the slag cooler and the corresponding variation amount of the material bed differential pressure variation rate is as follows:
wherein i is the number of groups of stationary data,
is the sampling average value of the regulating quantity S of the slag cooler, and Delta S is the regulating quantity change of the slag cooler, Delta V p The change rate of the material layer pressure difference is the change quantity.
Accordingly, FIG. 2 shows the variation Δ V of the rate of change of the material bed pressure difference p The material layer differential pressure change rate change quantity delta V can be seen from the scatter diagram between the material layer differential pressure change rate and the material layer differential pressure change rate delta S of the slag cooler p And the change quantity delta S of the regulating quantity of the slag cooler is inversely related.
further, step 4 specifically includes:
step 41, sequencing the quantity of change of the regulating quantity of the slag cooler, grouping and aggregating data of the sequenced quantity of change of the regulating quantity of the slag cooler according to a preset numerical interval, and recording the grouped data as a regulating quantity fitting data group;
it should be noted that the number of data in any group of adjustment quantity fitting data groups may be the same or different, but the difference value between the maximum value and the minimum value is within the range of the preset numerical interval, so as to realize the grouping aggregation of the adjustment quantity variation of the slag cooler.
Preferably, step 41 further comprises: and deleting the adjustment quantity fitting data group of which the data number is less than the number threshold value in the adjustment quantity fitting data group. That is, if the number threshold is set to 3, an array in which the number of data in the adjustment amount fitting data group is less than 3 is deleted.
As shown in fig. 3, the adjustment quantity of the slag cooler after grouping polymerization and the change quantity of the material layer differential pressure change rate show obvious correlation.
Step 42, calculating the median of the variation of the material layer differential pressure variation rate corresponding to any group of adjustment quantity fitting data groups, recording the median as differential pressure fitting data, calculating the median of the adjustment quantity variation of the slag cooler corresponding to the group of adjustment quantity fitting data groups, and recording the median as adjustment quantity fitting data;
in this embodiment, when data are aggregated in each group, the median of the variation rate of the pressure difference of the material layer in the group and the median of the variation amount of the adjustment amount of the slag cooler are selected, and as the aggregation result of the group, each group is aggregated into one piece of data.
And 43, generating a pressure difference-regulating quantity curve by adopting a fitting mode according to the regulating quantity fitting data and the pressure difference fitting data.
Specifically, as shown in FIG. 4, the change amount Δ V is calculated according to the change rate of the material layer pressure difference p The parameter Δ S is an independent variable, and the parameter Δ S is a dependent variable, that is, the data of the independent variable and the dependent variable used for fitting the data are data after grouping polymerization, the independent variable is a material layer pressure difference change rate after polymerization, and the dependent variable is a parameter after polymerization.
The machine learning unitary intercept-free algorithm is used for establishing a regression model for fitting operation, and a corresponding unitary intercept-free equation can be described as follows:
y＝a×x
in the formula, a is a regression coefficient. The specific fitting process is not described in detail.
And 5, determining the adjustment quantity of the target slag cooler on a pressure difference-adjustment quantity curve according to the target value of the variation rate of the pressure difference of the material bed, wherein the adjustment quantity of the target slag cooler is used for controlling the bottom slag discharge of the slag cooler.
As shown in fig. 5 and 6, the predicted effect of the model can be demonstrated by comparison. Specifically, a slag cooler control model is established by using boiler production data, and the relation between the material bed differential pressure change rate variable quantity and the slag cooler regulating quantity is obtained; obtaining the change rate of the differential pressure of the target material layer through the set differential pressure of the target material layer, the differential pressure of the current material layer and a certain differential pressure change reaction time; and then calculating in real time to obtain the current material bed differential pressure change rate, wherein the difference between the target and the current is the material bed differential pressure change rate variable quantity, and obtaining the quantitative value of the regulating quantity of the slag cooler through model prediction. In the actual control of the slag cooler, the stable moment of the primary air fan and the coal feeder after being adjusted for a period of time is selected in real time, and the opening degree of a slag discharging door of the slag cooler is controlled by using the adjustment value. The quantitative control method through the model has the advantages of self-learning, feedforward and quantification.
The technical scheme of the application is explained in detail in the above with reference to the accompanying drawings, and the application provides a quantitative control method of a slag cooler, and the method comprises the following steps: step 1, acquiring production data of a boiler at each sampling time point and corresponding material layer pressure difference, and recording the production data in a sampling time period as a group of stable data when the maximum difference value of the production data in the sampling time period is judged to be less than or equal to a first stable threshold value, wherein the production data at least comprises the adjustment quantity of a slag cooler, the adjustment quantity of a coal feeder and the adjustment quantity of a primary air fan; step 2, calculating the sampling average value of the adjustment quantity of the slag cooler in each group of stable data and the material layer pressure difference change rate of the material layer pressure difference corresponding to the sampling time period; step 3, respectively calculating the coal feeder maximum difference value of the coal feeder regulating quantity and the fan maximum difference value of the primary fan regulating quantity in the two adjacent groups of stable data, when the coal feeder maximum difference value and the fan maximum difference value are judged to be smaller than or equal to a second stable threshold value, calculating the difference value of the sampling average values corresponding to the two adjacent groups of stable data, recording the difference value as the regulating quantity of the slag cooler regulating quantity, and calculating the corresponding material layer pressure difference change rate variable quantity; step 4, grouping and aggregating data according to the regulating quantity change quantity of the slag cooler and the material layer differential pressure change rate change quantity, and generating a differential pressure-regulating quantity curve in a fitting mode; and 5, determining the adjustment quantity of the target slag cooler on a pressure difference-adjustment quantity curve according to the target value of the variation rate of the pressure difference of the material bed, wherein the adjustment quantity of the target slag cooler is used for controlling the bottom slag discharge of the slag cooler. Through the technical scheme in this application, with the control parameter of bed of material pressure difference as cold sediment machine end sediment discharge capacity, solved the current cold sediment machine end sediment discharge capacity poor problem of control accuracy to the untimely possibility of sediment has been reduced to arrange.
The steps in the present application may be sequentially adjusted, combined, and subtracted according to actual requirements.
The units in the device can be merged, divided and deleted according to actual requirements.
Although the present application has been disclosed in detail with reference to the accompanying drawings, it is to be understood that such description is merely illustrative and not restrictive of the application of the present application. The scope of the present application is defined by the appended claims and may include various modifications, adaptations, and equivalents of the subject invention without departing from the scope and spirit of the present application.
Claims (7)
1. A quantitative control method for a slag cooler is characterized by comprising the following steps:
step 1, acquiring production data of a boiler at each sampling time point and corresponding material layer pressure difference, and recording each production data in one sampling time period as a group of stable data when the maximum difference value of each production data in one sampling time period is judged to be less than or equal to a first stable threshold value, wherein the production data at least comprises the adjustment quantity of a slag cooler, the adjustment quantity of a coal feeder and the adjustment quantity of a primary air fan;
step 2, calculating the sampling average value of the adjustment quantity of the slag cooler in each group of stable data and the material layer pressure difference change rate of the material layer pressure difference corresponding to the sampling time period;
step 3, respectively calculating the coal feeder maximum difference value of the coal feeder regulating quantity and the fan maximum difference value of the primary fan regulating quantity in the two adjacent groups of stable data, when the coal feeder maximum difference value and the fan maximum difference value are judged to be smaller than or equal to a second stable threshold value, calculating the difference value of the sampling average values corresponding to the two adjacent groups of stable data, recording the difference value as the regulating quantity of the slag cooler regulating quantity, and calculating the corresponding material layer pressure difference change rate variable quantity;
step 4, grouping and aggregating data according to the regulating quantity change quantity of the slag cooler and the material layer differential pressure change rate change quantity, and generating a differential pressure-regulating quantity curve in a fitting mode;
and 5, determining a target slag cooler regulating quantity on the pressure difference-regulating quantity curve according to the target value of the variation rate of the pressure difference of the material bed, wherein the target slag cooler regulating quantity is used for controlling the bottom slag discharge capacity of the slag cooler.
2. The quantitative control method for the slag cooler according to claim 1, wherein the step 1 further comprises: judging whether the maximum difference value of each production data in a sampling time period is less than or equal to a first stable threshold value, wherein the process specifically comprises the following steps:
respectively selecting the maximum value and the minimum value of each production data in the sampling time period, recording the difference value between the maximum value and the minimum value as the maximum difference value, and calculating the average value of each production data;
calculating the product of the average value and the fluctuation proportion and recording the product as the first stable threshold value;
and judging whether the maximum difference value is smaller than or equal to the first stable threshold value, if so, recording each production data in one sampling time period as a group of stable data, and if not, deleting each production data in the sampling time period.
3. The slag cooler quantitative control method according to claim 1, wherein in the step 2, calculating a material layer pressure difference change rate corresponding to a material layer pressure difference of a sampling time period specifically comprises:
selecting pressure difference starting data and pressure difference ending data corresponding to the material layer pressure difference within a preset time window range at the beginning and the end of the sampling time period respectively;
respectively calculating a first average value of the pressure difference starting data and a second average value of the pressure difference ending data;
and calculating the change rate of the material layer pressure difference according to the difference value between the first average value and the second average value.
4. The quantitative control method for the slag cooler according to claim 1, wherein the second smooth threshold includes a feeder smooth threshold and a fan smooth threshold, and the step 3 specifically includes:
respectively selecting the maximum value and the minimum value of the coal feeder regulating quantity and the primary air fan regulating quantity in two adjacent groups of stable data, calculating the difference value between the maximum value and the minimum value in the coal feeder regulating quantity, recording the difference value as the maximum coal feeder difference value, calculating the difference value between the maximum value and the minimum value of the primary air fan regulating quantity, and recording the difference value as the maximum air fan difference value;
calculating the average value of the adjustment quantity of the coal feeder and the average value of the adjustment quantity of the primary air fan, recording the product of the average value of the adjustment quantity of the coal feeder and the fluctuation ratio as the stable threshold value of the coal feeder, and recording the product of the average value of the adjustment quantity of the primary air fan and the fluctuation ratio as the stable threshold value of the air fan;
and judging whether the maximum difference value of the coal machine is less than or equal to the stable threshold value of the coal machine and whether the maximum difference value of the fan is less than or equal to the stable threshold value of the fan, if so, calculating the difference value of the two adjacent groups of stable data corresponding to the sampling average value, recording the variation of the adjustment quantity of the slag cooler, calculating the variation of the corresponding material layer pressure difference variation rate, and if not, deleting the two adjacent groups of stable data.
5. The quantitative control method for the slag cooler according to claim 1 or 4, characterized in that in the step 3, the method further comprises: and when the adjustment quantity change quantity of the slag cooler or the material layer pressure difference change rate change quantity is judged to be smaller than a preset threshold value, deleting the adjustment quantity change quantity of the slag cooler and the corresponding material layer pressure difference change rate change quantity.
6. The quantitative control method for the slag cooler according to claim 1, wherein the step 4 specifically comprises:
step 41, sorting the regulating quantity changing quantities of the slag cooler, grouping and aggregating data of the sorted regulating quantity changing quantities of the slag cooler according to a preset numerical value interval, and recording as a regulating quantity fitting data group;
step 42, calculating the median of the variation of the material layer differential pressure variation rate corresponding to any group of the adjustment quantity fitting data groups, recording the median as differential pressure fitting data, calculating the median of the adjustment quantity variation of the slag cooler corresponding to the adjustment quantity fitting data groups, and recording the median as adjustment quantity fitting data;
and 43, generating the differential pressure-regulating quantity curve in a fitting mode according to the regulating quantity fitting data and the differential pressure fitting data.
7. The quantitative control method for the slag cooler according to claim 6, wherein the step 41 further comprises:
and deleting the adjustment quantity fitting data group of which the number of data is less than the number threshold in the adjustment quantity fitting data group.
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