A temperature control method and system for ignition furnace of sintering machine

Abstract

The present application discloses a temperature control method and system for a sintering machine ignition furnace. The method first obtains the initial temperature value and set temperature value of the sintering machine ignition furnace; then obtains the gas flow set value through the DMC predictive control model; at the same time, optimizes the air-fuel ratio model through data analysis to obtain the optimal air-fuel ratio; obtains the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace; finally, controls the gas regulating valve according to the gas flow set value and the current gas flow measurement value; at the same time, controls the air regulating valve according to the current air flow set value and the current air flow measurement value. The method ensures that the amount of gas used in the ignition furnace is more accurate, more stable, and more economical. In the realization of automatic furnace burning, it can ensure that the automatic furnace burning adjusts the gas volume to a smaller range, improves the intelligence of the equipment, reduces the workers' misoperation, reduces the gas consumption, reduces the return rate and fuel rate, and increases the quality and strength of the ore.

Description

Technical Field

[0001] The invention relates to the technical field of automatic control, and in particular to a temperature control method and system for an ignition furnace of a sintering machine. Background Art

[0002] In the metallurgical industry, the sintering process is the pre-process of ironmaking production, an indispensable and important link in the entire steel industry production, and the raw material preparation process for subsequent ironmaking production. The sintering machine ignition furnace is the main device in the sintering process, and its function is to ignite the fuel in the mixed material on the sintering machine trolley. The ignition effect of the sintering machine directly affects the output and quality of the sintered ore and the energy consumption level of the sintering process.

[0003] In the working process of the existing sintering machine ignition furnace, there are the following problems:

[0004] (1) Since the sintering ignition furnace provides the combustion temperature for the mixed material on the sintering belt, it is difficult to control the temperature accuracy in time due to the change of the calorific value of the gas and the external interference of the site itself. As a result, the sintered ore may be over-burned or under-burned, and the sintering quality cannot meet the requirements of the blast furnace for the ore, affecting the production stability and output economy of the blast furnace.

[0005] (2) Due to the interference of external uncertain factors, such as changes in the speed of the sintering trolley, frequent fluctuations in gas pressure and other factors, the ignition intensity is too low or too high, which cannot guarantee the quality of the sintered ore and also causes energy waste.

[0006] (3) Most of the sintering on-site ignition furnaces are manually controlled or use traditional control methods, which not only consumes the labor intensity of workers, but also cannot ensure the stability of the furnace temperature. Summary of the invention

[0007] Based on this, the embodiment of the present application provides a method and system for controlling the temperature of a sintering machine ignition furnace, which can effectively solve the problems of under-burning and over-burning of sintered materials caused by the instability of the temperature in the furnace due to external interference, as well as the lag in controlling the temperature, and ensure that the amount of gas used in the ignition furnace is more accurate, more stable, and more economical. The realization of automatic furnace burning can ensure that the amount of gas adjusted by the automatic furnace burning is smaller, improve the intelligence of the equipment, reduce the misoperation of workers, reduce gas consumption, reduce the return rate and fuel rate, and increase the quality and strength of the ore.

[0008] In a first aspect, a method for controlling the temperature of an ignition furnace of a sintering machine is provided, the method comprising:

[0009] S1, obtaining the initial temperature value and set temperature value of the sintering machine ignition furnace;

[0010] S2, according to the initial temperature value and the set temperature value, the gas flow set value is obtained through the DMC predictive control model; at the same time, according to the initial temperature value, the air-fuel ratio model is optimized through data analysis to obtain the optimal air-fuel ratio;

[0011] S3, obtaining the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace;

[0012] S4, controls the gas regulating valve of the sintering machine ignition furnace according to the gas flow setting value and the current gas flow measurement value; at the same time, determines the current air flow setting value based on the optimal air-fuel ratio and the current gas flow measurement value, and controls the air regulating valve of the sintering machine ignition furnace according to the current air flow setting value and the current air flow measurement value.

[0013] Optionally, the DMC predictive control model specifically includes:

[0014] Set the parameter cycle and the number of samples collected;

[0015] Collect the data of the sintering machine ignition furnace based on the set parameter period, and pre-process the data to obtain a valid data set;

[0016] Predict the output value through the prediction sub-model;

[0017] Optimize the model parameters under the current constraints by rolling optimization sub-models;

[0018] The predicted output value is corrected through the feedback correction sub-model.

[0019] Optionally, the prediction sub-model specifically includes:

[0020] The output prediction value is determined by a first formula, wherein the first formula specifically includes:

[0021]

[0022] in, represents the output prediction value, represents the predicted initial value at time k for time k+i, Δu m =[Δu(k)Δu(k+1)...Δu(k+m-1)] T It means that at time k, there are m continuous control increments.

[0023] Optionally, the rolling optimization sub-model specifically includes:

[0024] The vector form of the model parameters is determined as

[0025]

[0026] in, m represents the number of control increments, p represents the length of the predicted output time domain, Represents the predicted output value of the controlled object at p moments in the future, y sp Indicates the current expected value;

[0027] The model parameters under the current constraint conditions are optimized by the second formula, wherein the second formula specifically includes:

[0028] u(k)=u(k-1)+Δu(k)

[0029] in, u(k) and u(k-1) represent the model parameters before and after optimization, respectively.

[0030] Optionally, the feedback correction sub-model specifically includes:

[0031] Obtain k predicted output values ​​according to the prediction sub-model;

[0032] Determine the error between the actual output and the predicted output at time k+1, and perform weighted correction;

[0033] The results after weighting method correction The elements of are shifted to form the initial value at time k+1, thereby correcting the predicted output value at time k+1.

[0034] Optionally, the data analysis and optimization of the air-fuel ratio model specifically includes:

[0035] The actual air-fuel ratio is collected according to a preset period, and the collected data is processed to obtain a time series of the actual air-fuel ratio;

[0036] The average value of the actual air-fuel ratio in the time series is calculated as the current optimized air-fuel ratio;

[0037] The optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment.

[0038] Optionally, obtaining the optimal air-fuel ratio based on the current optimized air-fuel ratio and the last optimized air-fuel ratio includes:

[0039] Allocate the weight ratio between the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment;

[0040] The optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio of the corresponding weight and the optimized air-fuel ratio at the previous moment.

[0041] In a second aspect, a sintering machine ignition furnace temperature control system is provided, the system comprising:

[0042] The first acquisition module is used to obtain the initial temperature value and the set temperature value of the sintering machine ignition furnace;

[0043] A processing module is used to obtain a gas flow setting value through a DMC predictive control model according to an initial temperature value and a set temperature value; and to obtain an optimal air-fuel ratio through a data analysis and optimization air-fuel ratio model according to the initial temperature value;

[0044] The second acquisition module acquires the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace;

[0045] The control module controls the gas regulating valve of the sintering machine ignition furnace according to the gas flow setting value and the current gas flow measurement value; at the same time, the current air flow setting value is determined based on the optimal air-fuel ratio and the current gas flow measurement value, and the air regulating valve of the sintering machine ignition furnace is controlled according to the current air flow setting value and the current air flow measurement value.

[0046] Optionally, the DMC predictive control model specifically includes:

[0047] Set the parameter cycle and the number of samples collected;

[0048] Collect the data of the sintering machine ignition furnace based on the set parameter period, and pre-process the data to obtain a valid data set;

[0049] Predict the output value through the prediction sub-model;

[0050] Optimize the model parameters under the current constraints by rolling optimization sub-models;

[0051] The predicted output value is corrected through the feedback correction sub-model.

[0052] Optionally, the data analysis and optimization of the air-fuel ratio model specifically includes:

[0053] The actual air-fuel ratio is collected according to a preset period, and the collected data is processed to obtain a time series of the actual air-fuel ratio;

[0054] The average value of the actual air-fuel ratio in the time series is calculated as the current optimized air-fuel ratio;

[0055] The optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment.

[0056] In the technical solution provided by the embodiment of the present application, the initial temperature value and the set temperature value of the sintering machine ignition furnace are first obtained; then the gas flow set value is obtained through the DMC predictive control model according to the initial temperature value and the set temperature value; at the same time, the optimal air-fuel ratio is obtained by optimizing the air-fuel ratio model through data analysis according to the initial temperature value; the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace are obtained; finally, the gas regulating valve of the sintering machine ignition furnace is controlled according to the gas flow set value and the current gas flow measurement value; at the same time, the current air flow set value is determined based on the optimal air-fuel ratio and the current gas flow measurement value, and the air regulating valve of the sintering machine ignition furnace is controlled according to the current air flow set value and the current air flow measurement value. It can be seen that the beneficial effects of the present invention are:

[0057] (1) The problem of furnace temperature stability during the ignition furnace burning process is solved, ensuring better quality and strength of sintered ore and reducing fuel efficiency.

[0058] (2) It solves the problem of rational utilization of gas volume and maximizes the heat storage of gas per unit time, ensuring gas saving and reducing CO emissions.

[0059] (3) The problem of no gas composition measuring instrument and inaccurate reliance on the measuring instrument is solved, ensuring the most reasonable and suitable air-fuel ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0061] Figure 1 A flow chart of a sintering machine ignition furnace temperature control method provided in an embodiment of the present application;

[0062] Figure 2 A DMC predictive control model processing flow chart provided in an embodiment of the present application;

[0063] Figure 3 A schematic diagram of data collection in a DMC predictive control model provided in an embodiment of the present application;

[0064] Figure 4 A structural diagram of the DMC predictive control model system provided in the embodiment of the present application;

[0065] Figure 5 A flow chart of the optimized air-fuel ratio model processing provided in the embodiment of the present application;

[0066] Figure 6 A temperature and actual air-fuel ratio curve diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0068] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two. The terms "first" and "second" in the specification and claims of the present invention and the above-mentioned drawings are intended to distinguish the objects referred to. For schemes with a sequential flow, this terminology does not have to be understood as describing a specific order or sequence. For schemes with device structures, this terminology does not distinguish between importance, positional relationships, etc.

[0069] In addition, the terms "comprises", "has" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that have been explicitly listed, but may also include other steps or units that are not explicitly listed but are inherent to these processes, methods, products or apparatuses, or steps or units that are added based on further optimization schemes conceived by the present invention.

[0070] This application is applied to the ignition furnace of the sintering machine of the metallurgical enterprise. The purpose is to solve the problems of under-burning and over-burning of sintered ore caused by the unstable temperature in the furnace due to external interference, and the lag in controlling the temperature, and to ensure that the amount of gas used in the ignition furnace is more accurate, more stable and more economical. The realization of automatic furnace burning can ensure that the automatic furnace burning can adjust the gas volume to a smaller range, improve the intelligence of the equipment, reduce the workers' misoperation, reduce gas consumption, reduce the return rate and fuel rate, and increase the quality and strength of the ore. For details, please refer to Figure 1 , which shows a flow chart of a sintering machine ignition furnace temperature control method provided by an embodiment of the present application, the method may include the following steps:

[0071] S1, obtaining the initial temperature value and set temperature value of the sintering machine ignition furnace.

[0072] In the present application, the initial temperature value (ie, temperature PV) and the set temperature value (temperature SP) of the sintering machine ignition furnace are firstly obtained, wherein the obtained temperature may refer to the dome temperature of the sintering machine ignition furnace.

[0073] S2, according to the initial temperature value and the set temperature value, the gas flow set value is obtained through the DMC predictive control model; at the same time, according to the initial temperature value, the air-fuel ratio model is optimized through data analysis to obtain the optimal air-fuel ratio.

[0074] In the embodiments of the present application, Figure 2 , a DMC predictive control model processing flow chart is given, which includes: setting the parameter cycle and the number of collected samples; collecting the data of the sintering machine ignition furnace based on the set parameter cycle, and preprocessing the data to obtain a valid data set; predicting the output value through the prediction sub-model; optimizing the model parameters under the current constraints through the rolling optimization sub-model; and correcting the predicted output value through the feedback correction sub-model.

[0075] Specifically: The specific establishment process of the three sub-models in the DMC predictive control model of this application is as follows:

[0076] (1) Establishing a prediction sub-model

[0077] like Figure 3 , by collecting data sets, starting at time k, the number of n is as follows: a k =y k ,a k+t =y k+t ,a k+2t =y k+2t ,a k+3t =y k+3t

[0078] a k+4t =y k+4t ,...,a k+it =y k+it ,...,a k+nt =y k+nt

[0079] Building the Response Vector If k = 1 and period t = 1, then we have n is the modeling time domain.

[0080] According to the proportional and superposition properties of the linear system, m is the control time domain length, p is the predicted output time domain length, and n is the modeling time domain length, where m≤p≤n.

[0081] The initial value predicted at time k for time k+i is

[0082] Therefore, at time k, if there are m continuous control increments Δu m =[Δu(k) Δu(k+1) ... Δu(k+m-1)] T , acting on the object, the prediction model for outputting the predicted value at the next n moments is:

[0083]

[0084] The prediction sub-model is:

[0085] Where:

[0086] , represents the output prediction value, represents the predicted initial value at time k for time k+i,

[0087] (2) Establishing a rolling optimization sub-model

[0088] Through the prediction model, the predicted output value of the controlled object at p moments in the future can be obtained under m control increments. As close to y as possible sp ,y sp is the current expected value.

[0089] Then the optimization performance index at time k can be:

[0090]

[0091] in: is the error term Control quantity change term q i and γ j is the weight coefficient, which plays a role in suppressing the change of error value and control quantity.

[0092] The vector form of the performance index is:

[0093]

[0094] Where:

[0095] Substitute the above formula into J Δu (k) takes the minimum value, that is,

[0096] Then we have: From this we can see that the optimal solution for each control increment is:

[0097]

[0098] d T =C(A T Q1A+Q2) -1 A T Q1=[d1,d2,...,d p ],C=[1,0,0,...,0]

[0099] That is, the actual control consisting of the control increment is:

[0100] u(k)=u(k-1)+Δu(k)

[0101] (3) Feedback Correction Submodel

[0102] The feedback model corrects the predicted output value and the output impact of uncertain factors, and can be used to predict future output errors to supplement model-based predictions.

[0103] For the actual input, adding a Δu(k) step, the above formula can be used to calculate the predicted output value under its action:

[0104]

[0105] Where:

[0106]

[0107] At time k+1, the error between the actual output and the predicted output is:

[0108]

[0109] For the weighted method correction, we have:

[0110]

[0111] Where:

[0112]

[0113] At time k+1, due to the change of the time base point, the predicted future time point will also shift to k+2,…,k+n+1. The elements of are shifted to form the initial value at time k+1.

[0114] Therefore, the vector formula is:

[0115] Where:

[0116] In summary, if Figure 4 A structural diagram of the DMC predictive control model system provided in an embodiment of the present application is given.

[0117] For the optimized air-fuel ratio model of this application, Figure 5 , a flow chart of the optimized air-fuel ratio model processing provided for an embodiment of the present application is given.

[0118] Through the change of j, the actual air-fuel ratio corresponding to the temperature when the dome temperature rises is collected, and a certain number of collected air-fuel ratios are processed in a certain way.

[0119] The actual dome temperature and the actual air-fuel ratio are filtered to meet the requirement of dome temperature smoothing, and the part where the dome temperature rises is marked. Mark 1 means the corresponding actual air-fuel ratio is collected, and mark 0 means no data value is collected.

[0120] like Figure 6 The temperature and actual air-fuel ratio curve is shown in the figure above. From the figure, we can see that when the length is selected as l, the actual air-fuel ratio krb1, krb2, ..., krb is collected according to a certain period T when the mark 1 is obtained. m ,…Take a set of data as an example, when the condition meets mark 1, record the data, as shown in Table 1, which gives the corresponding actual air-fuel ratio of different interval periods.

[0121] Table 1

[0122]

[0123] The collected data is processed, and the first 10% and the last 10% of the processed data are deleted. Finally, the new actual air-fuel ratio time series is organized as krb1, krb2, ..., krb j , where j=80%l, l≥30.

[0124] Calculate yhkrb=(krb1+krb2+…+krb j ) / j

[0125] The air-fuel ratio involved in controlling is: kzkrb

[0126] Among them: the current optimized air-fuel ratio is yhkrb, the air-fuel ratio at the last moment is skrb, kzkrb is the default value during initialization, and mark 1 is b.

[0127] The actual air-fuel ratio is collected according to the preset period, and the collected data is processed to obtain the actual air-fuel ratio time series; the average value of the actual air-fuel ratio in the time series is calculated as the current optimized air-fuel ratio; and the optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment. Among them, the optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment with the corresponding weights. The following is an implementation process of allocating weights of 0.8 and 0.2:

[0128] Method calculation: if yhkrb>0andb then

[0129] skrb=kzkrb;

[0130] kzkrb=0.8*yhkrb+0.2*skrb;

[0131] End_if

[0132] S3, obtaining the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace.

[0133] S4, controls the gas regulating valve of the sintering machine ignition furnace according to the gas flow setting value and the current gas flow measurement value; at the same time, determines the current air flow setting value based on the optimal air-fuel ratio and the current gas flow measurement value, and controls the air regulating valve of the sintering machine ignition furnace according to the current air flow setting value and the current air flow measurement value.

[0134] In the embodiment of the present application, the gas regulating valve is controlled according to the comparison value of the gas flow setting value / measured value, and the air regulating valve is controlled according to the comparison value of the air flow setting value / measured value. Specifically, PID control can be used.

[0135] Specifically, a PID controller is a controller that combines an error signal with proportional, integral, and differential functions. In a sintering machine ignition furnace, a PID controller works by receiving the difference (i.e., error signal) between the actual temperature value measured from the temperature sensor and the set desired temperature value. The PID controller calculates a control signal based on this error signal, which is sent to the heating element to adjust the temperature in the ignition furnace.

[0136] Specifically, the PID controller performs the following steps:

[0137] Proportional control: Multiply the error signal by the proportional coefficient Kp to generate an output signal.

[0138] Integral control: The error signal is accumulated and scaled according to the integration time Ti to generate an output signal.

[0139] Differential control: The error signal is differentiated and multiplied by the differential time Td to scale and generate an output signal.

[0140] The three output signals are added together to generate the final control signal.

[0141] This control signal will be converted into a voltage or current signal to adjust the temperature in the ignition furnace by controlling the power of the heating element. When the actual temperature reaches the set temperature, the error signal is close to zero and the controller will no longer generate an output signal.

[0142] Therefore, the PID controller plays an extremely important role in the sintering machine ignition furnace to ensure that the temperature in the ignition furnace is always within the required range.

[0143] The present application also provides a sintering machine ignition furnace temperature control system. The system includes:

[0144] The first acquisition module is used to obtain the initial temperature value and the set temperature value of the sintering machine ignition furnace;

[0145] A processing module is used to obtain a gas flow setting value through a DMC predictive control model according to an initial temperature value and a set temperature value; and to obtain an optimal air-fuel ratio through a data analysis and optimization air-fuel ratio model according to the initial temperature value;

[0146] The second acquisition module acquires the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace;

[0147] The control module controls the gas regulating valve of the sintering machine ignition furnace according to the gas flow setting value and the current gas flow measurement value; at the same time, the current air flow setting value is determined based on the optimal air-fuel ratio and the current gas flow measurement value, and the air regulating valve of the sintering machine ignition furnace is controlled according to the current air flow setting value and the current air flow measurement value.

[0148] In an optional embodiment of the present application, the DMC predictive control model specifically includes: setting a parameter cycle and the number of samples collected; collecting data of the sintering machine ignition furnace based on the set parameter cycle, and preprocessing the data to obtain a valid data set; predicting an output value through a prediction sub-model;

[0149] The model parameters under the current constraints are optimized through the rolling optimization sub-model; the predicted output value is corrected through the feedback correction sub-model.

[0150] In an optional embodiment of the present application, the data analysis optimization air-fuel ratio model specifically includes: collecting the actual air-fuel ratio according to a preset period, processing the collected data to obtain an actual air-fuel ratio time series; calculating the average value of the actual air-fuel ratio in the time series as the current optimized air-fuel ratio; and obtaining the optimal air-fuel ratio based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment.

[0151] A sintering machine ignition furnace temperature control system provided in an embodiment of the present application is used to implement the above-mentioned sintering machine ignition furnace temperature control method. For the specific definition of a sintering machine ignition furnace temperature control system, please refer to the definition of a sintering machine ignition furnace temperature control method in the above text, which will not be repeated here. Each part of the above-mentioned sintering machine ignition furnace temperature control system can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the device in hardware form, or can be stored in the memory in the device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0152] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0153] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A method for controlling the temperature of a sintering machine ignition furnace, characterized in that: The method comprises: S1, obtaining the initial temperature value and set temperature value of the sintering machine ignition furnace; S2, according to the initial temperature value and the set temperature value, the gas flow set value is obtained through the DMC predictive control model; at the same time, according to the initial temperature value, the air-fuel ratio model is optimized through data analysis to obtain the optimal air-fuel ratio; S3, obtaining the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace; S4, controlling the gas regulating valve of the ignition furnace of the sintering machine according to the gas flow setting value and the current gas flow measurement value; at the same time, determining the current air flow setting value based on the optimal air-fuel ratio and the current gas flow measurement value, and controlling the air regulating valve of the ignition furnace of the sintering machine according to the current air flow setting value and the current air flow measurement value; The data analysis and optimization air-fuel ratio model specifically includes: collecting the actual air-fuel ratio according to a preset period, processing the collected data to obtain an actual air-fuel ratio time series; calculating the average value of the actual air-fuel ratio in the time series as the current optimized air-fuel ratio; and obtaining the optimal air-fuel ratio based on the current optimized air-fuel ratio and the previous moment optimized air-fuel ratio; The optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment, including: allocating a weight ratio of the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment; and obtaining the optimal air-fuel ratio according to the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment with corresponding weights.

2. A sintering machine ignition furnace temperature control method according to claim 1, characterized in that: The DMC predictive control model specifically includes: Set the parameter cycle and the number of samples collected; Collect the data of the sintering machine ignition furnace based on the set parameter period, and pre-process the data to obtain a valid data set; Predict the output value through the prediction sub-model; Optimize the model parameters under the current constraints by rolling optimization sub-models; The predicted output value is corrected through the feedback correction sub-model.

3. A sintering machine ignition furnace temperature control method according to claim 2, characterized in that: The prediction sub-model specifically includes: The output prediction value is determined by a first formula, wherein the first formula specifically includes: in, represents the output prediction value, represents the predicted initial value at time k for time k+i, Δu m =[Δu(k)Δu(k+1)...Δu(k+m-1)] T It means that at time k, there are m continuous control increments.

4. The method for controlling the temperature of a sintering machine ignition furnace according to claim 2, characterized in that: The rolling optimization sub-model specifically includes: The vector form of the model parameters is determined as in, m represents the number of control increments, p represents the length of the predicted output time domain, Represents the predicted output value of the controlled object at p moments in the future, y sp Indicates the current expected value; The model parameters under the current constraint conditions are optimized by the second formula, wherein the second formula specifically includes: u(k)=u(k-1)+Δu(k) in, u(k) and u(k-1) represent the model parameters before and after optimization, respectively.

5. The method for controlling the temperature of a sintering machine ignition furnace according to claim 2, characterized in that: The feedback correction sub-model specifically includes: Obtain k predicted output values ​​according to the prediction sub-model; Determine the error between the actual output and the predicted output at time k+1, and perform weighted correction; The result y after weighted method correction new The element shift of (k+1) forms the initial value at time k+1, thereby correcting the predicted output value at time k+1.

6. A temperature control system for a sintering machine ignition furnace, characterized in that: The system comprises: The first acquisition module is used to obtain the initial temperature value and the set temperature value of the sintering machine ignition furnace; A processing module is used to obtain a gas flow setting value through a DMC predictive control model according to an initial temperature value and a set temperature value; and to obtain an optimal air-fuel ratio through a data analysis and optimization air-fuel ratio model according to the initial temperature value; The second acquisition module acquires the current gas flow measurement value and the current air flow measurement value of the sintering machine ignition furnace; The control module controls the gas regulating valve of the ignition furnace of the sintering machine according to the gas flow setting value and the current gas flow measurement value; at the same time, the current air flow setting value is determined based on the optimal air-fuel ratio and the current gas flow measurement value, and the air regulating valve of the ignition furnace of the sintering machine is controlled according to the current air flow setting value and the current air flow measurement value; The data analysis and optimization air-fuel ratio model specifically includes: collecting the actual air-fuel ratio according to a preset period, processing the collected data to obtain an actual air-fuel ratio time series; calculating the average value of the actual air-fuel ratio in the time series as the current optimized air-fuel ratio; and obtaining the optimal air-fuel ratio based on the current optimized air-fuel ratio and the previous moment optimized air-fuel ratio; The optimal air-fuel ratio is obtained based on the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment, including: allocating a weight ratio of the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment; and obtaining the optimal air-fuel ratio according to the current optimized air-fuel ratio and the optimized air-fuel ratio at the previous moment with corresponding weights.

7. A sintering machine ignition furnace temperature control system according to claim 6, characterized in that: The DMC predictive control model specifically includes: Set the parameter cycle and the number of samples collected; Collect the data of the sintering machine ignition furnace based on the set parameter period, and pre-process the data to obtain a valid data set; Predict the output value through the prediction sub-model; Optimize the model parameters under the current constraints by rolling optimization sub-models; The predicted output value is corrected through the feedback correction sub-model.

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